POLARIZED LINE FORMATION IN NON-MONOTONIC VELOCITY FIELDS

Energy Technology Data Exchange (ETDEWEB)

Sampoorna, M.; Nagendra, K. N., E-mail: sampoorna@iiap.res.in, E-mail: knn@iiap.res.in [Indian Institute of Astrophysics, Koramangala, Bengaluru 560034 (India)

2016-12-10

For a correct interpretation of the observed spectro-polarimetric data from astrophysical objects such as the Sun, it is necessary to solve the polarized line transfer problems taking into account a realistic temperature structure, the dynamical state of the atmosphere, a realistic scattering mechanism (namely, the partial frequency redistribution—PRD), and the magnetic fields. In a recent paper, we studied the effects of monotonic vertical velocity fields on linearly polarized line profiles formed in isothermal atmospheres with and without magnetic fields. However, in general the velocity fields that prevail in dynamical atmospheres of astrophysical objects are non-monotonic. Stellar atmospheres with shocks, multi-component supernova atmospheres, and various kinds of wave motions in solar and stellar atmospheres are examples of non-monotonic velocity fields. Here we present studies on the effect of non-relativistic non-monotonic vertical velocity fields on the linearly polarized line profiles formed in semi-empirical atmospheres. We consider a two-level atom model and PRD scattering mechanism. We solve the polarized transfer equation in the comoving frame (CMF) of the fluid using a polarized accelerated lambda iteration method that has been appropriately modified for the problem at hand. We present numerical tests to validate the CMF method and also discuss the accuracy and numerical instabilities associated with it.

Non-monotonic effect of growth temperature on carrier collection in SnS solar cells

International Nuclear Information System (INIS)

Chakraborty, R.; Steinmann, V.; Mangan, N. M.; Brandt, R. E.; Poindexter, J. R.; Jaramillo, R.; Mailoa, J. P.; Hartman, K.; Polizzotti, A.; Buonassisi, T.; Yang, C.; Gordon, R. G.

2015-01-01

We quantify the effects of growth temperature on material and device properties of thermally evaporated SnS thin-films and test structures. Grain size, Hall mobility, and majority-carrier concentration monotonically increase with growth temperature. However, the charge collection as measured by the long-wavelength contribution to short-circuit current exhibits a non-monotonic behavior: the collection decreases with increased growth temperature from 150 °C to 240 °C and then recovers at 285 °C. Fits to the experimental internal quantum efficiency using an opto-electronic model indicate that the non-monotonic behavior of charge-carrier collection can be explained by a transition from drift- to diffusion-assisted components of carrier collection. The results show a promising increase in the extracted minority-carrier diffusion length at the highest growth temperature of 285 °C. These findings illustrate how coupled mechanisms can affect early stage device development, highlighting the critical role of direct materials property measurements and simulation

Nonmonotonic belief state frames and reasoning frames

NARCIS (Netherlands)

Engelfriet, J.; Herre, H.; Treur, J.

1995-01-01

In this paper five levels of specification of nonmonotonic reasoning are distinguished. The notions of semantical frame, belief state frame and reasoning frame are introduced and used as a semantical basis for the first three levels. Moreover, the semantical connections between the levels are

Modelling Embedded Systems by Non-Monotonic Refinement

NARCIS (Netherlands)

Mader, Angelika H.; Marincic, J.; Wupper, H.

2008-01-01

This paper addresses the process of modelling embedded sys- tems for formal verification. We propose a modelling process built on non-monotonic refinement and a number of guidelines. The outcome of the modelling process is a model, together with a correctness argument that justifies our modelling

Nonmonotonic critical temperature in superconductor ferromagnet bilayers

NARCIS (Netherlands)

Fominov, Ya. V.; Fominov, I.V.; Chtchelkatchev, N.M.; Golubov, Alexandre Avraamovitch

2002-01-01

The critical temperature Tc of a superconductor/ferromagnet (SF) bilayer can exhibit nonmonotonic dependence on the thickness df of the F layer. SF systems have been studied for a long time; according to the experimental situation, a ¿dirty¿ limit is often considered which implies that the mean free

Non-monotone positive solutions of second-order linear differential equations: existence, nonexistence and criteria

Directory of Open Access Journals (Sweden)

Mervan Pašić

2016-10-01

Full Text Available We study non-monotone positive solutions of the second-order linear differential equations: $(p(tx'' + q(t x = e(t$, with positive $p(t$ and $q(t$. For the first time, some criteria as well as the existence and nonexistence of non-monotone positive solutions are proved in the framework of some properties of solutions $\\theta (t$ of the corresponding integrable linear equation: $(p(t\\theta''=e(t$. The main results are illustrated by many examples dealing with equations which allow exact non-monotone positive solutions not necessarily periodic. Finally, we pose some open questions.

Non-monotonic probability of thermal reversal in thin-film biaxial nanomagnets with small energy barriers

Directory of Open Access Journals (Sweden)

N. Kani

2017-05-01

Full Text Available The goal of this paper is to investigate the short time-scale, thermally-induced probability of magnetization reversal for an biaxial nanomagnet that is characterized with a biaxial magnetic anisotropy. For the first time, we clearly show that for a given energy barrier of the nanomagnet, the magnetization reversal probability of an biaxial nanomagnet exhibits a non-monotonic dependence on its saturation magnetization. Specifically, there are two reasons for this non-monotonic behavior in rectangular thin-film nanomagnets that have a large perpendicular magnetic anisotropy. First, a large perpendicular anisotropy lowers the precessional period of the magnetization making it more likely to precess across the x^=0 plane if the magnetization energy exceeds the energy barrier. Second, the thermal-field torque at a particular energy increases as the magnitude of the perpendicular anisotropy increases during the magnetization precession. This non-monotonic behavior is most noticeable when analyzing the magnetization reversals on time-scales up to several tens of ns. In light of the several proposals of spintronic devices that require data retention on time-scales up to 10’s of ns, understanding the probability of magnetization reversal on the short time-scales is important. As such, the results presented in this paper will be helpful in quantifying the reliability and noise sensitivity of spintronic devices in which thermal noise is inevitably present.

Adaptive increase in force variance during fatigue in tasks with low redundancy.

Science.gov (United States)

Singh, Tarkeshwar; S K M, Varadhan; Zatsiorsky, Vladimir M; Latash, Mark L

2010-11-26

We tested a hypothesis that fatigue of an element (a finger) leads to an adaptive neural strategy that involves an increase in force variability in the other finger(s) and an increase in co-variation of commands to fingers to keep total force variability relatively unchanged. We tested this hypothesis using a system with small redundancy (two fingers) and a marginally redundant system (with an additional constraint related to the total moment of force produced by the fingers, unstable condition). The subjects performed isometric accurate rhythmic force production tasks by the index (I) finger and two fingers (I and middle, M) pressing together before and after a fatiguing exercise by the I finger. Fatigue led to a large increase in force variance in the I-finger task and a smaller increase in the IM-task. We quantified two components of variance in the space of hypothetical commands to fingers, finger modes. Under both stable and unstable conditions, there was a large increase in the variance component that did not affect total force and a much smaller increase in the component that did. This resulted in an increase in an index of the force-stabilizing synergy. These results indicate that marginal redundancy is sufficient to allow the central nervous system to use adaptive increase in variability to shield important variables from effects of fatigue. We offer an interpretation of these results based on a recent development of the equilibrium-point hypothesis known as the referent configuration hypothesis. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

A Mathematical Model for Non-monotonic Deposition Profiles in Deep Bed Filtration Systems

DEFF Research Database (Denmark)

Yuan, Hao; Shapiro, Alexander

2011-01-01

A mathematical model for suspension/colloid flow in porous media and non-monotonic deposition is proposed. It accounts for the migration of particles associated with the pore walls via the second energy minimum (surface associated phase). The surface associated phase migration is characterized...... by advection and diffusion/dispersion. The proposed model is able to produce a nonmonotonic deposition profile. A set of methods for estimating the modeling parameters is provided in the case of minimal particle release. The estimation can be easily performed with available experimental information....... The numerical modeling results highly agree with the experimental observations, which proves the ability of the model to catch a non-monotonic deposition profile in practice. An additional equation describing a mobile population behaving differently from the injected population seems to be a sufficient...

Nonmonotonic Trust Management for P2P Applications

NARCIS (Netherlands)

Czenko, M.R.; Tran, H.M.; Doumen, J.M.; Etalle, Sandro; Hartel, Pieter H.; den Hartog, Jeremy

Community decisions about access control in virtual communities are non-monotonic in nature. This means that they cannot be expressed in current, monotonic trust management languages such as the family of Role Based Trust Management languages (RT). To solve this problem we propose RTo, which adds a

Information flow in layered networks of non-monotonic units

International Nuclear Information System (INIS)

Neves, Fabio Schittler; Schubert, Benno Martim; Erichsen, Rubem Jr

2015-01-01

Layered neural networks are feedforward structures that yield robust parallel and distributed pattern recognition. Even though much attention has been paid to pattern retrieval properties in such systems, many aspects of their dynamics are not yet well characterized or understood. In this work we study, at different temperatures, the memory activity and information flows through layered networks in which the elements are the simplest binary odd non-monotonic function. Our results show that, considering a standard Hebbian learning approach, the network information content has its maximum always at the monotonic limit, even though the maximum memory capacity can be found at non-monotonic values for small enough temperatures. Furthermore, we show that such systems exhibit rich macroscopic dynamics, including not only fixed point solutions of its iterative map, but also cyclic and chaotic attractors that also carry information. (paper)

Information flow in layered networks of non-monotonic units

Science.gov (United States)

Schittler Neves, Fabio; Martim Schubert, Benno; Erichsen, Rubem, Jr.

2015-07-01

Layered neural networks are feedforward structures that yield robust parallel and distributed pattern recognition. Even though much attention has been paid to pattern retrieval properties in such systems, many aspects of their dynamics are not yet well characterized or understood. In this work we study, at different temperatures, the memory activity and information flows through layered networks in which the elements are the simplest binary odd non-monotonic function. Our results show that, considering a standard Hebbian learning approach, the network information content has its maximum always at the monotonic limit, even though the maximum memory capacity can be found at non-monotonic values for small enough temperatures. Furthermore, we show that such systems exhibit rich macroscopic dynamics, including not only fixed point solutions of its iterative map, but also cyclic and chaotic attractors that also carry information.

Increasing the genetic variance of rice protein through mutation breeding techniques

International Nuclear Information System (INIS)

Ismachin, M.

1975-01-01

Recommended rice variety in Indonesia, Pelita I/1 was treated with gamma rays at the doses of 20 krad, 30 krad, and 40 krad. The seeds were also treated with EMS 1%. In M 2 generation, the protein content of seeds from the visible mutants and from the normal looking plants were analyzed by DBC method. No significant increase in the genetic variance was found on the samples treated with 20 krad gamma, and on the normal looking plants treated by EMS 1%. The mean value of the treated samples were mostly significant decrease compared with the mean value of the protein distribution in untreated samples (control). Since significant increase in genetic variance was also found in M 2 normal looking plants - treated with gamma at the doses of 30 krad and 40 krad -selection of protein among these materials could be more valuable. (author)

Non-monotonic field dependence of critical current in composite superconductors

International Nuclear Information System (INIS)

Andrianov, V.V.; Baev, V.P.; Ivanov, S.S.

1982-01-01

The nonmonotonic field dependence of critical current Im(B/sub a/ in composite superconductors is investigated experimentally for current and field varying simultaneously with final rates I and B/sub a/

A Nonmonotone Line Search Filter Algorithm for the System of Nonlinear Equations

Directory of Open Access Journals (Sweden)

Zhong Jin

2012-01-01

Full Text Available We present a new iterative method based on the line search filter method with the nonmonotone strategy to solve the system of nonlinear equations. The equations are divided into two groups; some equations are treated as constraints and the others act as the objective function, and the two groups are just updated at the iterations where it is needed indeed. We employ the nonmonotone idea to the sufficient reduction conditions and filter technique which leads to a flexibility and acceptance behavior comparable to monotone methods. The new algorithm is shown to be globally convergent and numerical experiments demonstrate its effectiveness.

Adding a Parameter Increases the Variance of an Estimated Regression Function

Science.gov (United States)

Withers, Christopher S.; Nadarajah, Saralees

2011-01-01

The linear regression model is one of the most popular models in statistics. It is also one of the simplest models in statistics. It has received applications in almost every area of science, engineering and medicine. In this article, the authors show that adding a predictor to a linear model increases the variance of the estimated regression…

Theoretical and experimental study of non-monotonous effects

International Nuclear Information System (INIS)

Delforge, J.

1977-01-01

In recent years, the study of the effects of low dose rates has expanded considerably, especially in connection with current problems concerning the environment and health physics. After having made a precise definition of the different types of non-monotonous effect which may be encountered, for each the main experimental results known are indicated, as well as the principal consequences which may be expected. One example is the case of radiotherapy, where there is a chance of finding irradiation conditions such that the ratio of destructive action on malignant cells to healthy cells is significantly improved. In the second part of the report, the appearance of these phenomena, especially at low dose rates are explained. For this purpose, the theory of transformation systems of P. Delattre is used as a theoretical framework. With the help of a specific example, it is shown that non-monotonous effects are frequently encountered, especially when the overall effect observed is actually the sum of several different elementary effects (e.g. in survival curves, where death may be due to several different causes), or when the objects studied possess inherent kinetics not limited to restoration phenomena alone (e.g. cellular cycle) [fr

Nonmonotonic reasoning in description logics. Rational closure for the ABox

CSIR Research Space (South Africa)

Casini, G

2013-07-01

Full Text Available The introduction of defeasible reasoning in Description Logics has been a main research topic in the field in the last years. Despite the fact that various interesting formalizations of nonmonotonic reasoning for the TBox have been proposed...

Genetic selection for increased mean and reduced variance of twinning rate in Belclare ewes.

Science.gov (United States)

Cottle, D J; Gilmour, A R; Pabiou, T; Amer, P R; Fahey, A G

2016-04-01

It is sometimes possible to breed for more uniform individuals by selecting animals with a greater tendency to be less variable, that is, those with a smaller environmental variance. This approach has been applied to reproduction traits in various animal species. We have evaluated fecundity in the Irish Belclare sheep breed by analyses of flocks with differing average litter size (number of lambs per ewe per year, NLB) and have estimated the genetic variance in environmental variance of lambing traits using double hierarchical generalized linear models (DHGLM). The data set comprised of 9470 litter size records from 4407 ewes collected in 56 flocks. The percentage of pedigreed lambing ewes with singles, twins and triplets was 30, 54 and 14%, respectively, in 2013 and has been relatively constant for the last 15 years. The variance of NLB increases with the mean in this data; the correlation of mean and standard deviation across sires is 0.50. The breeding goal is to increase the mean NLB without unduly increasing the incidence of triplets and higher litter sizes. The heritability estimates for lambing traits were NLB, 0.09; triplet occurrence (TRI) 0.07; and twin occurrence (TWN), 0.02. The highest and lowest twinning flocks differed by 23% (75% versus 52%) in the proportion of ewes lambing twins. Fitting bivariate sire models to NLB and the residual from the NLB model using a double hierarchical generalized linear model (DHGLM) model found a strong genetic correlation (0.88 ± 0.07) between the sire effect for the magnitude of the residual (VE ) and sire effects for NLB, confirming the general observation that increased average litter size is associated with increased variability in litter size. We propose a threshold model that may help breeders with low litter size increase the percentage of twin bearers without unduly increasing the percentage of ewes bearing triplets in Belclare sheep. © 2015 Blackwell Verlag GmbH.

Multigenerational contaminant exposures produce non-monotonic, transgenerational responses in Daphnia magna

International Nuclear Information System (INIS)

Kimberly, David A.; Salice, Christopher J.

2015-01-01

Generally, ecotoxicologists rely on short-term tests that assume populations to be static. Conversely, natural populations may be exposed to the same stressors for many generations, which can alter tolerance to the same (or other) stressors. The objective of this study was to improve our understanding of how multigenerational stressors alter life history traits and stressor tolerance. After continuously exposing Daphnia magna to cadmium for 120 days, we assessed life history traits and conducted a challenge at higher temperature and cadmium concentrations. Predictably, individuals exposed to cadmium showed an overall decrease in reproductive output compared to controls. Interestingly, control D. magna were the most cadmium tolerant to novel cadmium, followed by those exposed to high cadmium. Our data suggest that long-term exposure to cadmium alter tolerance traits in a non-monotonic way. Because we observed effects after one-generation removal from cadmium, transgenerational effects may be possible as a result of multigenerational exposure. - Highlights: • Daphnia magna exposed to cadmium for 120 days. • D. magna exposed to cadmium had decreased reproductive output. • Control D. magna were most cadmium tolerant to novel cadmium stress. • Long-term exposure to cadmium alter tolerance traits in a non-monotonic way. • Transgenerational effects observed as a result of multigenerational exposure. - Adverse effects of long-term cadmium exposure persist into cadmium free conditions, as seen by non-monotonic responses when exposed to novel stress one generation removed.

Nonmonotonic low frequency losses in HTSCs

International Nuclear Information System (INIS)

Castro, H; Gerber, A; Milner, A

2007-01-01

A calorimetric technique has been used in order to study ac-field dissipation in ceramic BSCCO samples at low frequencies between 0.05 and 250 Hz, at temperatures from 65 to 90 K. In contrast to previous studies, where ac losses have been reported with a linear dependence on magnetic field frequency, we find a nonmonotonic function presenting various maxima. Frequencies corresponding to local maxima of dissipation depend on the temperature and the amplitude of the ac magnetic field. Flux creep is argued to be responsible for this behaviour. A simple model connecting the characteristic vortex relaxation times (flux creep) and the location of dissipation maxima versus frequency is proposed

Non-monotonic resonance in a spatially forced Lengyel-Epstein model

Energy Technology Data Exchange (ETDEWEB)

Haim, Lev [Physics Department, Ben-Gurion University of the Negev, Beer-Sheva 84105 (Israel); Department of Oncology, Soroka University Medical Center, Beer-Sheva 84101 (Israel); Hagberg, Aric [Center for Nonlinear Studies, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States); Meron, Ehud [Physics Department, Ben-Gurion University of the Negev, Beer-Sheva 84105 (Israel); Department of Solar Energy and Environmental Physics, BIDR, Ben-Gurion University of the Negev, Sede Boqer Campus, Midreshet Ben-Gurion 84990 (Israel)

2015-06-15

We study resonant spatially periodic solutions of the Lengyel-Epstein model modified to describe the chlorine dioxide-iodine-malonic acid reaction under spatially periodic illumination. Using multiple-scale analysis and numerical simulations, we obtain the stability ranges of 2:1 resonant solutions, i.e., solutions with wavenumbers that are exactly half of the forcing wavenumber. We show that the width of resonant wavenumber response is a non-monotonic function of the forcing strength, and diminishes to zero at sufficiently strong forcing. We further show that strong forcing may result in a π/2 phase shift of the resonant solutions, and argue that the nonequilibrium Ising-Bloch front bifurcation can be reversed. We attribute these behaviors to an inherent property of forcing by periodic illumination, namely, the increase of the mean spatial illumination as the forcing amplitude is increased.

Non-monotonic reasoning in conceptual modeling and ontology design: A proposal

CSIR Research Space (South Africa)

Casini, G

2013-06-01

Full Text Available -1 2nd International Workshop on Ontologies and Conceptual Modeling (Onto.Com 2013), Valencia, Spain, 17-21 June 2013 Non-monotonic reasoning in conceptual modeling and ontology design: A proposal Giovanni Casini1 and Alessandro Mosca2 1...

Nonmonotonic and anisotropic magnetoresistance effect in antiferromagnet CaMn2Bi2

Science.gov (United States)

Kawaguchi, N.; Urata, T.; Hatano, T.; Iida, K.; Ikuta, H.

2018-04-01

We found a large and unique magnetoresistance (MR) effect for CaMn2Bi2 . When the magnetic field was applied along the crystallographic c axis at low temperatures, the resistivity increased with the magnetic field and the MR ratio reached several hundred percent, but then it decreased with further increasing the applied field. In addition, the angle dependence measurement revealed a strong anisotropy. This compound is an antiferromagnetic semiconductor with a narrow band gap, and Mn atoms form a corrugated honeycomb lattice. Therefore, a frustration among the magnetic moments is expected, and we propose that our observations can be understood by a nonmonotonic modulation of magnetic fluctuation under the magnetic field.

Increased gender variance in autism spectrum disorders and attention deficit hyperactivity disorder.

Science.gov (United States)

Strang, John F; Kenworthy, Lauren; Dominska, Aleksandra; Sokoloff, Jennifer; Kenealy, Laura E; Berl, Madison; Walsh, Karin; Menvielle, Edgardo; Slesaransky-Poe, Graciela; Kim, Kyung-Eun; Luong-Tran, Caroline; Meagher, Haley; Wallace, Gregory L

2014-11-01

Evidence suggests over-representation of autism spectrum disorders (ASDs) and behavioral difficulties among people referred for gender issues, but rates of the wish to be the other gender (gender variance) among different neurodevelopmental disorders are unknown. This chart review study explored rates of gender variance as reported by parents on the Child Behavior Checklist (CBCL) in children with different neurodevelopmental disorders: ASD (N = 147, 24 females and 123 males), attention deficit hyperactivity disorder (ADHD; N = 126, 38 females and 88 males), or a medical neurodevelopmental disorder (N = 116, 57 females and 59 males), were compared with two non-referred groups [control sample (N = 165, 61 females and 104 males) and non-referred participants in the CBCL standardization sample (N = 1,605, 754 females and 851 males)]. Significantly greater proportions of participants with ASD (5.4%) or ADHD (4.8%) had parent reported gender variance than in the combined medical group (1.7%) or non-referred comparison groups (0-0.7%). As compared to non-referred comparisons, participants with ASD were 7.59 times more likely to express gender variance; participants with ADHD were 6.64 times more likely to express gender variance. The medical neurodevelopmental disorder group did not differ from non-referred samples in likelihood to express gender variance. Gender variance was related to elevated emotional symptoms in ADHD, but not in ASD. After accounting for sex ratio differences between the neurodevelopmental disorder and non-referred comparison groups, gender variance occurred equally in females and males.

Laser induced non-monotonic degradation in short-circuit current of triple-junction solar cells

Science.gov (United States)

Dou, Peng-Cheng; Feng, Guo-Bin; Zhang, Jian-Min; Song, Ming-Ying; Zhang, Zhen; Li, Yun-Peng; Shi, Yu-Bin

2018-06-01

In order to study the continuous wave (CW) laser radiation effects and mechanism of GaInP/GaAs/Ge triple-junction solar cells (TJSCs), 1-on-1 mode irradiation experiments were carried out. It was found that the post-irradiation short circuit current (ISC) of the TJSCs initially decreased and then increased with increasing of irradiation laser power intensity. To explain this phenomenon, a theoretical model had been established and then verified by post-damage tests and equivalent circuit simulations. Conclusion was drawn that laser induced alterations in the surface reflection and shunt resistance were the main causes for the observed non-monotonic decrease in the ISC of the TJSCs.

On-line learning of non-monotonic rules by simple perceptron

OpenAIRE

Inoue, Jun-ichi; Nishimori, Hidetoshi; Kabashima, Yoshiyuki

1997-01-01

We study the generalization ability of a simple perceptron which learns unlearnable rules. The rules are presented by a teacher perceptron with a non-monotonic transfer function. The student is trained in the on-line mode. The asymptotic behaviour of the generalization error is estimated under various conditions. Several learning strategies are proposed and improved to obtain the theoretical lower bound of the generalization error.

Non-monotonic wetting behavior of chitosan films induced by silver nanoparticles

Energy Technology Data Exchange (ETDEWEB)

Praxedes, A.P.P.; Webler, G.D.; Souza, S.T. [Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió, AL (Brazil); Ribeiro, A.S. [Instituto de Química e Biotecnologia, Universidade Federal de Alagoas, 57072-970 Maceió, AL (Brazil); Fonseca, E.J.S. [Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió, AL (Brazil); Oliveira, I.N. de, E-mail: italo@fis.ufal.br [Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió, AL (Brazil)

2016-05-01

Highlights: • The addition of silver nanoparticles modifies the morphology of chitosan films. • Metallic nanoparticles can be used to control wetting properties of chitosan films. • The contact angle shows a non-monotonic dependence on the silver concentration. - Abstract: The present work is devoted to the study of structural and wetting properties of chitosan-based films containing silver nanoparticles. In particular, the effects of silver concentration on the morphology of chitosan films are characterized by different techniques, such as atomic force microscopy (AFM), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). By means of dynamic contact angle measurements, we study the modification on surface properties of chitosan-based films due to the addition of silver nanoparticles. The results are analyzed in the light of molecular-kinetic theory which describes the wetting phenomena in terms of statistical dynamics for the displacement of liquid molecules in a solid substrate. Our results show that the wetting properties of chitosan-based films are high sensitive to the fraction of silver nanoparticles, with the equilibrium contact angle exhibiting a non-monotonic behavior.

Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theories

OpenAIRE

Wałęga, Przemysław Andrzej; Schultz, Carl; Bhatt, Mehul

2016-01-01

The systematic modelling of dynamic spatial systems is a key requirement in a wide range of application areas such as commonsense cognitive robotics, computer-aided architecture design, and dynamic geographic information systems. We present ASPMT(QS), a novel approach and fully-implemented prototype for non-monotonic spatial reasoning -a crucial requirement within dynamic spatial systems- based on Answer Set Programming Modulo Theories (ASPMT). ASPMT(QS) consists of a (qualitative) spatial re...

Surfactants non-monotonically modify the onset of Faraday waves

Science.gov (United States)

Strickland, Stephen; Shearer, Michael; Daniels, Karen

2017-11-01

When a water-filled container is vertically vibrated, subharmonic Faraday waves emerge once the driving from the vibrations exceeds viscous dissipation. In the presence of an insoluble surfactant, a viscous boundary layer forms at the contaminated surface to balance the Marangoni and Boussinesq stresses. For linear gravity-capillary waves in an undriven fluid, the surfactant-induced boundary layer increases the amount of viscous dissipation. In our analysis and experiments, we consider whether similar effects occur for nonlinear Faraday (gravity-capillary) waves. Assuming a finite-depth, infinite-breadth, low-viscosity fluid, we derive an analytic expression for the onset acceleration up to second order in ɛ =√{ 1 / Re } . This expression allows us to include fluid depth and driving frequency as parameters, in addition to the Marangoni and Boussinesq numbers. For millimetric fluid depths and driving frequencies of 30 to 120 Hz, our analysis recovers prior numerical results and agrees with our measurements of NBD-PC surfactant on DI water. In both case, the onset acceleration increases non-monotonically as a function of Marangoni and Boussinesq numbers. For shallower systems, our model predicts that surfactants could decrease the onset acceleration. DMS-0968258.

Subtractive, divisive and non-monotonic gain control in feedforward nets linearized by noise and delays.

Science.gov (United States)

Mejias, Jorge F; Payeur, Alexandre; Selin, Erik; Maler, Leonard; Longtin, André

2014-01-01

The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry-also known as "open-loop feedback"-, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different regimes of gain control: subtractive, divisive, and non-monotonic. Subtractive gain control was obtained when noise is very low in the network. Also, it was possible to change from divisive to non-monotonic gain control by simply modulating the strength of the feedforward inhibition, which may be achieved via long-term synaptic plasticity. The particular case of divisive gain control has been previously observed in vivo in weakly electric fish. These gain control regimes were robust to the presence of temporal delays in the inhibitory feedforward pathway, which were found to linearize the input-to-output mappings (or f-I curves) via a novel variability-increasing mechanism. Our findings highlight the feedforward-induced gain control analyzed here as a highly versatile mechanism of information gating in the brain.

Subtractive, divisive and non-monotonic gain control in feedforward nets linearized by noise and delays

Directory of Open Access Journals (Sweden)

Jorge F Mejias

2014-02-01

Full Text Available The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry — also known as ’open-loop feedback’ —, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different regimes of gain control: subtractive, divisive, and non-monotonic. Subtractive gain control was obtained when noise is very low in the network. Also, it was possible to change from divisive to non-monotonic gain control by simply modulating the strength of the feedforward inhibition, which may be achieved via long-term synaptic plasticity. The particular case of divisive gain control has been previously observed in vivo in weakly electric fish. These gain control regimes were robust to the presence of temporal delays in the inhibitory feedforward pathway, which were found to linearize the input-to-output mappings (or f-I curves via a novel variability-increasing mechanism. Our findings highlight the feedforward-induced gain control analyzed here as a highly versatile mechanism of information gating in the brain.

Induction and Confirmation Theory: An Approach based on a Paraconsistent Nonmonotonic Logic

Directory of Open Access Journals (Sweden)

Ricardo Sousa Silvestre

2010-12-01

Full Text Available This paper is an effort to realize and explore the connections that exist between nonmonotonic logic and confirmation theory. We pick up one of the most wide-spread nonmonotonic formalisms – default logic – and analyze to what extent and under what adjustments it could work as a logic of induction in the philosophical sense. By making use of this analysis, we extend default logic so as to make it able to minimally perform the task of a logic of induction, having as a result a system which we believe has interesting properties from the standpoint of theory of confirmation. It is for instance able to represent chains of inductive rules as well as to reason paraconsistently on the conclusions obtained from them. We then use this logic to represent some traditional ideas concerning confirmation theory, in particular the ones proposed by Carl Hempel in his classical paper “Studies in the Logic of Confirmation” of 1945 and the ones incorporated in the so-called abductive and hy-pothetico-deductive models.

Induction and Confirmation Theory: An Approach based on a Paraconsistent Nonmonotonic Logic

Directory of Open Access Journals (Sweden)

Ricardo Sousa Silvestre

2011-05-01

Full Text Available This paper is an effort to realize and explore the connections that exist between nonmonotonic logic and confirmation theory. We pick up one of the most wide-spread nonmonotonic formalisms – default logic – and analyze to what extent and under what adjustments it could work as a logic of induction in the philosophical sense. By making use of this analysis, we extend default logic so as to make it able to minimally perform the task of a logic of induction, having as a result a system which we believe has interesting properties from the standpoint of theory of confirmation. It is for instance able to represent chains of inductive rules as well as to reason paraconsistently on the conclusions obtained from them. We then use this logic to represent some traditional ideas concerning confirmation theory, in particular the ones proposed by Carl Hempel in his classical paper "Studies in the Logic of Confirmation" of 1945 and the ones incorporated in the so-called abductive and hy-pothetico-deductive models.

Genetic Gain Increases by Applying the Usefulness Criterion with Improved Variance Prediction in Selection of Crosses.

Science.gov (United States)

Lehermeier, Christina; Teyssèdre, Simon; Schön, Chris-Carolin

2017-12-01

A crucial step in plant breeding is the selection and combination of parents to form new crosses. Genome-based prediction guides the selection of high-performing parental lines in many crop breeding programs which ensures a high mean performance of progeny. To warrant maximum selection progress, a new cross should also provide a large progeny variance. The usefulness concept as measure of the gain that can be obtained from a specific cross accounts for variation in progeny variance. Here, it is shown that genetic gain can be considerably increased when crosses are selected based on their genomic usefulness criterion compared to selection based on mean genomic estimated breeding values. An efficient and improved method to predict the genetic variance of a cross based on Markov chain Monte Carlo samples of marker effects from a whole-genome regression model is suggested. In simulations representing selection procedures in crop breeding programs, the performance of this novel approach is compared with existing methods, like selection based on mean genomic estimated breeding values and optimal haploid values. In all cases, higher genetic gain was obtained compared with previously suggested methods. When 1% of progenies per cross were selected, the genetic gain based on the estimated usefulness criterion increased by 0.14 genetic standard deviation compared to a selection based on mean genomic estimated breeding values. Analytical derivations of the progeny genotypic variance-covariance matrix based on parental genotypes and genetic map information make simulations of progeny dispensable, and allow fast implementation in large-scale breeding programs. Copyright © 2017 by the Genetics Society of America.

Oscillation of Nonlinear Delay Differential Equation with Non-Monotone Arguments

Directory of Open Access Journals (Sweden)

Özkan Öcalan

2017-07-01

Full Text Available Consider the first-order nonlinear retarded differential equation $$ x^{\\prime }(t+p(tf\\left( x\\left( \\tau (t\\right \\right =0, t\\geq t_{0} $$ where $p(t$ and $\\tau (t$ are function of positive real numbers such that $%\\tau (t\\leq t$ for$\\ t\\geq t_{0},\\ $and$\\ \\lim_{t\\rightarrow \\infty }\\tau(t=\\infty $. Under the assumption that the retarded argument is non-monotone, new oscillation results are given. An example illustrating the result is also given.

Female scarcity reduces women's marital ages and increases variance in men's marital ages.

Science.gov (United States)

Kruger, Daniel J; Fitzgerald, Carey J; Peterson, Tom

2010-08-05

When women are scarce in a population relative to men, they have greater bargaining power in romantic relationships and thus may be able to secure male commitment at earlier ages. Male motivation for long-term relationship commitment may also be higher, in conjunction with the motivation to secure a prospective partner before another male retains her. However, men may also need to acquire greater social status and resources to be considered marriageable. This could increase the variance in male marital age, as well as the average male marital age. We calculated the Operational Sex Ratio, and means, medians, and standard deviations in marital ages for women and men for the 50 largest Metropolitan Statistical Areas in the United States with 2000 U.S Census data. As predicted, where women are scarce they marry earlier on average. However, there was no significant relationship with mean male marital ages. The variance in male marital age increased with higher female scarcity, contrasting with a non-significant inverse trend for female marital age variation. These findings advance the understanding of the relationship between the OSR and marital patterns. We believe that these results are best accounted for by sex specific attributes of reproductive value and associated mate selection criteria, demonstrating the power of an evolutionary framework for understanding human relationships and demographic patterns.

Female Scarcity Reduces Women's Marital Ages and Increases Variance in Men's Marital Ages

Directory of Open Access Journals (Sweden)

Daniel J. Kruger

2010-07-01

Full Text Available When women are scarce in a population relative to men, they have greater bargaining power in romantic relationships and thus may be able to secure male commitment at earlier ages. Male motivation for long-term relationship commitment may also be higher, in conjunction with the motivation to secure a prospective partner before another male retains her. However, men may also need to acquire greater social status and resources to be considered marriageable. This could increase the variance in male marital age, as well as the average male marital age. We calculated the Operational Sex Ratio, and means, medians, and standard deviations in marital ages for women and men for the 50 largest Metropolitan Statistical Areas in the United States with 2000 U.S Census data. As predicted, where women are scarce they marry earlier on average. However, there was no significant relationship with mean male marital ages. The variance in male marital age increased with higher female scarcity, contrasting with a non-significant inverse trend for female marital age variation. These findings advance the understanding of the relationship between the OSR and marital patterns. We believe that these results are best accounted for by sex specific attributes of reproductive value and associated mate selection criteria, demonstrating the power of an evolutionary framework for understanding human relationships and demographic patterns.

Mapping axonal density and average diameter using non-monotonic time-dependent gradient-echo MRI

DEFF Research Database (Denmark)

Nunes, Daniel; Cruz, Tomás L; Jespersen, Sune N

2017-01-01

available in the clinic, or extremely long acquisition schemes to extract information from parameter-intensive models. In this study, we suggest that simple and time-efficient multi-gradient-echo (MGE) MRI can be used to extract the axon density from susceptibility-driven non-monotonic decay in the time...... the quantitative results are compared against ground-truth histology, they seem to reflect the axonal fraction (though with a bias, as evident from Bland-Altman analysis). As well, the extra-axonal fraction can be estimated. The results suggest that our model is oversimplified, yet at the same time evidencing......-dependent signal. We show, both theoretically and with simulations, that a non-monotonic signal decay will occur for multi-compartmental microstructures – such as axons and extra-axonal spaces, which we here used in a simple model for the microstructure – and that, for axons parallel to the main magnetic field...

Non-monotonic behaviour in relaxation dynamics of image restoration

International Nuclear Information System (INIS)

Ozeki, Tomoko; Okada, Masato

2003-01-01

We have investigated the relaxation dynamics of image restoration through a Bayesian approach. The relaxation dynamics is much faster at zero temperature than at the Nishimori temperature where the pixel-wise error rate is minimized in equilibrium. At low temperature, we observed non-monotonic development of the overlap. We suggest that the optimal performance is realized through premature termination in the relaxation processes in the case of the infinite-range model. We also performed Markov chain Monte Carlo simulations to clarify the underlying mechanism of non-trivial behaviour at low temperature by checking the local field distributions of each pixel

Evolution of Genetic Variance during Adaptive Radiation.

Science.gov (United States)

Walter, Greg M; Aguirre, J David; Blows, Mark W; Ortiz-Barrientos, Daniel

2018-04-01

Genetic correlations between traits can concentrate genetic variance into fewer phenotypic dimensions that can bias evolutionary trajectories along the axis of greatest genetic variance and away from optimal phenotypes, constraining the rate of evolution. If genetic correlations limit adaptation, rapid adaptive divergence between multiple contrasting environments may be difficult. However, if natural selection increases the frequency of rare alleles after colonization of new environments, an increase in genetic variance in the direction of selection can accelerate adaptive divergence. Here, we explored adaptive divergence of an Australian native wildflower by examining the alignment between divergence in phenotype mean and divergence in genetic variance among four contrasting ecotypes. We found divergence in mean multivariate phenotype along two major axes represented by different combinations of plant architecture and leaf traits. Ecotypes also showed divergence in the level of genetic variance in individual traits and the multivariate distribution of genetic variance among traits. Divergence in multivariate phenotypic mean aligned with divergence in genetic variance, with much of the divergence in phenotype among ecotypes associated with changes in trait combinations containing substantial levels of genetic variance. Overall, our results suggest that natural selection can alter the distribution of genetic variance underlying phenotypic traits, increasing the amount of genetic variance in the direction of natural selection and potentially facilitating rapid adaptive divergence during an adaptive radiation.

Nonmonotonic behaviour of superconducting critical temperature of Nb/CuNi bilayers with a nanometer range of layer thickness

International Nuclear Information System (INIS)

Morari, R.; Antropov, E.; Socrovisciuc, A.; Prepelitsa, A.; Zdravkov, V.I.; Tagirov, L.R.; Kupriyanov, M.Yu.; Sidorenko, A.S.

2009-01-01

Present work reports the result of the proximity effect investigation for superconducting Nb/CuNi-bilayers with the thickness of the ferromagnetic layer (Cu x Ni 1-x ) being in the sub-nanometer range. It was found a non-monotonic behavior of the critical temperature T c , i.e. its growth with the increasing of the ferromagnetic layer thickness dF, for the series of the samples with constant thickness of Nb layer, (d Nb = const). (authors)

Non-monotonic relationships between emotional arousal and memory for color and location.

Science.gov (United States)

Boywitt, C Dennis

2015-01-01

Recent research points to the decreased diagnostic value of subjective retrieval experience for memory accuracy for emotional stimuli. While for neutral stimuli rich recollective experiences are associated with better context memory than merely familiar memories this association appears questionable for emotional stimuli. The present research tested the implicit assumption that the effect of emotional arousal on memory is monotonic, that is, steadily increasing (or decreasing) with increasing arousal. In two experiments emotional arousal was manipulated in three steps using emotional pictures and subjective retrieval experience as well as context memory were assessed. The results show an inverted U-shape relationship between arousal and recognition memory but for context memory and retrieval experience the relationship was more complex. For frame colour, context memory decreased linearly while for spatial location it followed the inverted U-shape function. The complex, non-monotonic relationships between arousal and memory are discussed as possible explanations for earlier divergent findings.

Annealing temperature dependent non-monotonic d{sup 0} ferromagnetism in pristine In{sub 2}O{sub 3} nanoparticles

Energy Technology Data Exchange (ETDEWEB)

Cao, Haiming; Xing, Pengfei, E-mail: pfxing@tju.edu.cn; Yao, Dongsheng; Wu, Ping

2017-05-01

Cubic bixbyite In{sub 2}O{sub 3} nanoparticles with room temperature d{sup 0} ferromagnetism were prepared by sol-gel method with the air annealing temperature ranging from 500 to 900 °C. X-ray diffraction, X-ray photoelectron spectroscopy, Raman-scattering and photoluminescence were carried out to demonstrate the presence of oxygen vacancies. The lattice constant, the atomic ratio of crystal O and In, the Raman peak at 369 cm{sup −1}, the PL emission peak at 396 nm and the saturation magnetization of d{sup 0} ferromagnetism all had a consistent non-monotonic change with the increasing annealing temperature. With further considering the relation between the grain size and the distribution of oxygen vacancies, we think that d{sup 0} ferromagnetism in our samples is directly related with the singly charged oxygen vacancies at the surface of In{sub 2}O{sub 3} nanoparticles. - Highlights: • Effect of air-annealing temperature on the d{sup 0} ferromagnetism of pure In{sub 2}O{sub 3}. • Oxygen-deficiency states of all samples were detected by Raman scattering and PL. • Ferromagnetism changes non-monotonically with the increasing annealing temperature. • d{sup 0} ferromagnetism in our In{sub 2}O{sub 3} nanoparticles is related with the surface V{sub O}{sup +}.

Population Bottlenecks Increase Additive Genetic Variance But Do Not Break a Selection Limit in Rainforest Drosophila

DEFF Research Database (Denmark)

van Heerwaarden, Belinda; Willi, Yvonne; Kristensen, Torsten N

2008-01-01

for desiccation resistance in the rain forest-restricted fly Drosophila bunnanda. After one generation of single-pair mating, additive genetic variance for desiccation resistance increased to a significant level, on average higher than for the control lines. Line crosses revealed that both dominance and epistatic...

A zero-variance-based scheme for variance reduction in Monte Carlo criticality

Energy Technology Data Exchange (ETDEWEB)

Christoforou, S.; Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)

2006-07-01

A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)

A zero-variance-based scheme for variance reduction in Monte Carlo criticality

International Nuclear Information System (INIS)

Christoforou, S.; Hoogenboom, J. E.

2006-01-01

A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)

ASPMT(QS): Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theories

OpenAIRE

Wałęga, Przemysław Andrzej; Bhatt, Mehul; Schultz, Carl

2015-01-01

The systematic modelling of \\emph{dynamic spatial systems} [9] is a key requirement in a wide range of application areas such as comonsense cognitive robotics, computer-aided architecture design, dynamic geographic information systems. We present ASPMT(QS), a novel approach and fully-implemented prototype for non-monotonic spatial reasoning ---a crucial requirement within dynamic spatial systems-- based on Answer Set Programming Modulo Theories (ASPMT). ASPMT(QS) consists of a (qualitative) s...

Large Airborne Full Tensor Gradient Data Inversion Based on a Non-Monotone Gradient Method

Science.gov (United States)

Sun, Yong; Meng, Zhaohai; Li, Fengting

2018-03-01

Following the development of gravity gradiometer instrument technology, the full tensor gravity (FTG) data can be acquired on airborne and marine platforms. Large-scale geophysical data can be obtained using these methods, making such data sets a number of the "big data" category. Therefore, a fast and effective inversion method is developed to solve the large-scale FTG data inversion problem. Many algorithms are available to accelerate the FTG data inversion, such as conjugate gradient method. However, the conventional conjugate gradient method takes a long time to complete data processing. Thus, a fast and effective iterative algorithm is necessary to improve the utilization of FTG data. Generally, inversion processing is formulated by incorporating regularizing constraints, followed by the introduction of a non-monotone gradient-descent method to accelerate the convergence rate of FTG data inversion. Compared with the conventional gradient method, the steepest descent gradient algorithm, and the conjugate gradient algorithm, there are clear advantages of the non-monotone iterative gradient-descent algorithm. Simulated and field FTG data were applied to show the application value of this new fast inversion method.

Non-monotonic Pre-fixed Points and Learning

Directory of Open Access Journals (Sweden)

Stefano Berardi

2013-08-01

Full Text Available We consider the problem of finding pre-fixed points of interactive realizers over arbitrary knowledge spaces, obtaining a relative recursive procedure. Knowledge spaces and interactive realizers are an abstract setting to represent learning processes, that can interpret non-constructive proofs. Atomic pieces of information of a knowledge space are stratified into levels, and evaluated into truth values depending on knowledge states. Realizers are then used to define operators that extend a given state by adding and possibly removing atoms: in a learning process states of knowledge change nonmonotonically. Existence of a pre-fixed point of a realizer is equivalent to the termination of the learning process with some state of knowledge which is free of patent contradictions and such that there is nothing to add. In this paper we generalize our previous results in the case of level 2 knowledge spaces and deterministic operators to the case of omega-level knowledge spaces and of non-deterministic operators.

Non-monotonic dose-response relationships and endocrine disruptors: a qualitative method of assessment

OpenAIRE

Lagarde, Fabien; Beausoleil, Claire; Belcher, Scott M; Belzunces, Luc P; Emond, Claude; Guerbet, Michel; Rousselle, Christophe

2015-01-01

International audience; Experimental studies investigating the effects of endocrine disruptors frequently identify potential unconventional dose-response relationships called non-monotonic dose-response (NMDR) relationships. Standardized approaches for investigating NMDR relationships in a risk assessment context are missing. The aim of this work was to develop criteria for assessing the strength of NMDR relationships. A literature search was conducted to identify published studies that repor...

On the connection between nonmonotonic taste behavior and molecular conformation in solution: The case of rebaudioside-A

Science.gov (United States)

Chopade, Prashant D.; Sarma, Bipul; Santiso, Erik E.; Simpson, Jeffrey; Fry, John C.; Yurttas, Nese; Biermann, Kari L.; Chen, Jie; Trout, Bernhardt L.; Myerson, Allan S.

2015-12-01

The diterpene steviol glycoside, rebaudioside A, is a natural high potency non-caloric sweetener extracted from the leaves of Stevia rebaudiana. This compound shows a parabolic change in sweet taste intensity with temperature which contrasts with the general finding for other synthetic or natural sweeteners whose sweet taste increases with temperature. The nonmonotonic taste behavior was determined by sensory analysis using large taste panels. The conformational landscape of rebaudioside A was established at a range of temperatures by means of nuclear magnetic resonance and molecular dynamics simulation. The relationship between various conformations and the observed sweetness of rebaudioside A is described.

On the connection between nonmonotonic taste behavior and molecular conformation in solution: The case of rebaudioside-A

International Nuclear Information System (INIS)

Chopade, Prashant D.; Sarma, Bipul; Santiso, Erik E.; Chen, Jie; Trout, Bernhardt L.; Myerson, Allan S.; Simpson, Jeffrey; Fry, John C.; Biermann, Kari L.; Yurttas, Nese

2015-01-01

The diterpene steviol glycoside, rebaudioside A, is a natural high potency non-caloric sweetener extracted from the leaves of Stevia rebaudiana. This compound shows a parabolic change in sweet taste intensity with temperature which contrasts with the general finding for other synthetic or natural sweeteners whose sweet taste increases with temperature. The nonmonotonic taste behavior was determined by sensory analysis using large taste panels. The conformational landscape of rebaudioside A was established at a range of temperatures by means of nuclear magnetic resonance and molecular dynamics simulation. The relationship between various conformations and the observed sweetness of rebaudioside A is described

On the connection between nonmonotonic taste behavior and molecular conformation in solution: The case of rebaudioside-A

Energy Technology Data Exchange (ETDEWEB)

Chopade, Prashant D.; Sarma, Bipul; Santiso, Erik E.; Chen, Jie; Trout, Bernhardt L.; Myerson, Allan S., E-mail: myerson@mit.edu [Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 66-568, Cambridge, Massachusetts 02139 (United States); Simpson, Jeffrey [Department of Chemistry Instrumentation Facility, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 18-0090, Cambridge, Massachusetts 02139 (United States); Fry, John C.; Biermann, Kari L. [Connect Consulting, 6 Hollands Field, Horsham RH123HQ (United Kingdom); Yurttas, Nese [Cargill, Inc., Global Food Technology, 2301 Crosby Road, Wayzata, Minnesota 55391 (United States)

2015-12-28

The diterpene steviol glycoside, rebaudioside A, is a natural high potency non-caloric sweetener extracted from the leaves of Stevia rebaudiana. This compound shows a parabolic change in sweet taste intensity with temperature which contrasts with the general finding for other synthetic or natural sweeteners whose sweet taste increases with temperature. The nonmonotonic taste behavior was determined by sensory analysis using large taste panels. The conformational landscape of rebaudioside A was established at a range of temperatures by means of nuclear magnetic resonance and molecular dynamics simulation. The relationship between various conformations and the observed sweetness of rebaudioside A is described.

The non-monotonic shear-thinning flow of two strongly cohesive concentrated suspensions

OpenAIRE

Buscall, Richard; Kusuma, Tiara E.; Stickland, Anthony D.; Rubasingha, Sayuri; Scales, Peter J.; Teo, Hui-En; Worrall, Graham L.

2014-01-01

The behaviour in simple shear of two concentrated and strongly cohesive mineral suspensions showing highly non-monotonic flow curves is described. Two rheometric test modes were employed, controlled stress and controlled shear-rate. In controlled stress mode the materials showed runaway flow above a yield stress, which, for one of the suspensions, varied substantially in value and seemingly at random from one run to the next, such that the up flow-curve appeared to be quite irreproducible. Th...

Validation of consistency of Mendelian sampling variance.

Science.gov (United States)

Tyrisevä, A-M; Fikse, W F; Mäntysaari, E A; Jakobsen, J; Aamand, G P; Dürr, J; Lidauer, M H

2018-03-01

Experiences from international sire evaluation indicate that the multiple-trait across-country evaluation method is sensitive to changes in genetic variance over time. Top bulls from birth year classes with inflated genetic variance will benefit, hampering reliable ranking of bulls. However, none of the methods available today enable countries to validate their national evaluation models for heterogeneity of genetic variance. We describe a new validation method to fill this gap comprising the following steps: estimating within-year genetic variances using Mendelian sampling and its prediction error variance, fitting a weighted linear regression between the estimates and the years under study, identifying possible outliers, and defining a 95% empirical confidence interval for a possible trend in the estimates. We tested the specificity and sensitivity of the proposed validation method with simulated data using a real data structure. Moderate (M) and small (S) size populations were simulated under 3 scenarios: a control with homogeneous variance and 2 scenarios with yearly increases in phenotypic variance of 2 and 10%, respectively. Results showed that the new method was able to estimate genetic variance accurately enough to detect bias in genetic variance. Under the control scenario, the trend in genetic variance was practically zero in setting M. Testing cows with an average birth year class size of more than 43,000 in setting M showed that tolerance values are needed for both the trend and the outlier tests to detect only cases with a practical effect in larger data sets. Regardless of the magnitude (yearly increases in phenotypic variance of 2 or 10%) of the generated trend, it deviated statistically significantly from zero in all data replicates for both cows and bulls in setting M. In setting S with a mean of 27 bulls in a year class, the sampling error and thus the probability of a false-positive result clearly increased. Still, overall estimated genetic

Guest Controlled Nonmonotonic Deep Cavity Cavitand Assembly State Switching.

Science.gov (United States)

Tang, Du; Barnett, J Wesley; Gibb, Bruce C; Ashbaugh, Henry S

2017-11-30

Octa-acid (OA) and tetra-endo-methyl octa-acid (TEMOA) are water-soluble, deep-cavity cavitands with nanometer-sized nonpolar pockets that readily bind complementary guests, such as n-alkanes. Experimentally, OA exhibits a progression of 1:1 to 2:2 to 2:1 host/guest complexes (X:Y where X is the number of hosts and Y is the number of guests) with increasing alkane chain length from methane to tetradecane. Differing from OA only by the addition of four methyl groups ringing the portal of the pocket, TEMOA exhibits a nonmonotonic progression of assembly states from 1:1 to 2:2 to 1:1 to 2:1 with increasing guest length. Here we present a systematic molecular simulation study to parse the molecular and thermodynamic determinants that distinguish the succession of assembly stoichiometries observed for these similar hosts. Potentials of mean force between hosts and guests, determined via umbrella sampling, are used to characterize association free energies. These free energies are subsequently used in a reaction network model to predict the equilibrium distributions of assemblies. Our models accurately reproduce the experimentally observed trends, showing that TEMOA's endo-methyl units constrict the opening of the binding pocket, limiting the conformations available to bound guests and disrupting the balance between monomeric complexes and dimeric capsules. The success of our simulations demonstrate their utility at interpreting the impact of even simple chemical modifications on supramolecular assembly and highlight their potential to aid bottom-up design.

Nonmonotonic Behavior of Supermultiplet Pattern Formation in a Noisy Lotka-Volterra System

International Nuclear Information System (INIS)

Fiasconaro, A.; Valenti, D.; Spagnolo, B.

2004-01-01

The noise-induced pattern formation in a population dynamical model of three interacting species in the coexistence regime is investigated. A coupled map lattice of Lotka-Volterra equations in the presence of multiplicative noise is used to analyze the spatiotemporal evolution. The spatial correlation of the species concentration as a function of time and of the noise intensity is investigated. A nonmonotonic behavior of the area of the patterns as a function of both noise intensity and evolution time is found. (author)

How do people learn from negative evidence? Non-monotonic generalizations and sampling assumptions in inductive reasoning.

Science.gov (United States)

Voorspoels, Wouter; Navarro, Daniel J; Perfors, Amy; Ransom, Keith; Storms, Gert

2015-09-01

A robust finding in category-based induction tasks is for positive observations to raise the willingness to generalize to other categories while negative observations lower the willingness to generalize. This pattern is referred to as monotonic generalization. Across three experiments we find systematic non-monotonicity effects, in which negative observations raise the willingness to generalize. Experiments 1 and 2 show that this effect emerges in hierarchically structured domains when a negative observation from a different category is added to a positive observation. They also demonstrate that this is related to a specific kind of shift in the reasoner's hypothesis space. Experiment 3 shows that the effect depends on the assumptions that the reasoner makes about how inductive arguments are constructed. Non-monotonic reasoning occurs when people believe the facts were put together by a helpful communicator, but monotonicity is restored when they believe the observations were sampled randomly from the environment. Copyright © 2015 Elsevier Inc. All rights reserved.

Non-monotonic behavior of electron temperature in argon inductively coupled plasma and its analysis via novel electron mean energy equation

Science.gov (United States)

Zhao, Shu-Xia

2018-03-01

In this work, the behavior of electron temperature against the power in argon inductively coupled plasma is investigated by a fluid model. The model properly reproduces the non-monotonic variation of temperature with power observed in experiments. By means of a novel electron mean energy equation proposed for the first time in this article, this electron temperature behavior is interpreted. In the overall considered power range, the skin effect of radio frequency electric field results in localized deposited power density, responsible for an increase of electron temperature with power by means of one parameter defined as power density divided by electron density. At low powers, the rate fraction of multistep and Penning ionizations of metastables that consume electron energy two times significantly increases with power, which dominates over the skin effect and consequently leads to the decrease of temperature with power. In the middle power regime, a transition region of temperature is given by the competition between the ionizing effect of metastables and the skin effect of electric field. The power location where the temperature alters its trend moves to the low power end as increasing the pressure due to the lack of metastables. The non-monotonic curve of temperature is asymmetric at the short chamber due to the weak role of skin effect in increasing the temperature and tends symmetric when axially prolonging the chamber. Still, the validity of the fluid model in this prediction is estimated and the role of neutral gas heating is guessed. This finding is helpful for people understanding the different trends of temperature with power in the literature.

Application of non-monotonic logic to failure diagnosis of nuclear power plant

International Nuclear Information System (INIS)

Takahashi, M.; Kitamura, M.; Sugiyama, K.

1989-01-01

A prototype diagnosis system for nuclear power plants was developed based on Truth Maintenance systems: TMS and Dempster-Shafer probability theory. The purpose of this paper is to establish basic technique for more intelligent, man-computer cooperative diagnosis system. The developed system is capable of carrying out the diagnostic inference under the imperfect observation condition with the help of the proposed belief revision procedure with TMS and the systematic uncertainty treatment with Dempster-Shafer theory. The usefulness and potentiality of the present non-monotonic logic were demonstrated through simulation experiments

A Nonmonotone Trust Region Method for Nonlinear Programming with Simple Bound Constraints

International Nuclear Information System (INIS)

Chen, Z.-W.; Han, J.-Y.; Xu, D.-C.

2001-01-01

In this paper we propose a nonmonotone trust region algorithm for optimization with simple bound constraints. Under mild conditions, we prove the global convergence of the algorithm. For the monotone case it is also proved that the correct active set can be identified in a finite number of iterations if the strict complementarity slackness condition holds, and so the proposed algorithm reduces finally to an unconstrained minimization method in a finite number of iterations, allowing a fast asymptotic rate of convergence. Numerical experiments show that the method is efficient

Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

Science.gov (United States)

Dazard, Jean-Eudes; Rao, J Sunil

2012-07-01

The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

Cytotoxicity of binary mixtures of human pharmaceuticals in a fish cell line: approaches for non-monotonic concentration-response relationships.

Science.gov (United States)

Bain, Peter A; Kumar, Anupama

2014-08-01

Predicting the effects of mixtures of environmental micropollutants is a priority research area. In this study, the cytotoxicity of ten pharmaceuticals to the rainbow trout cell line RTG-2 was determined using the neutral red uptake assay. Fluoxetine (FL), propranolol (PPN), and diclofenac (DCF) were selected for further study as binary mixtures. Biphasic concentration-response relationships were observed in cells exposed to FL and PPN. In the case of PPN, microscopic examination revealed lysosomal swelling indicative of direct uptake and accumulation of the compound. Three equations describing non-monotonic concentration-response relationships were evaluated and one was found to consistently provide more accurate estimates of the median and 10% effect concentrations compared with a sigmoidal concentration-response model. Predictive modeling of the effects of binary mixtures of FL, PPN, and DCF was undertaken using an implementation of the concentration addition (CA) conceptual model incorporating non-monotonic concentration-response relationships. The cytotoxicity of the all three binary combinations could be adequately predicted using CA, suggesting that the toxic mode of action in RTG-2 cells is unrelated to the therapeutic mode of action of these compounds. The approach presented here is widely applicable to the study of mixture toxicity in cases where non-monotonic concentration-response relationships are observed. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Multistability of neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays.

Science.gov (United States)

Nie, Xiaobing; Zheng, Wei Xing

2015-05-01

This paper is concerned with the problem of coexistence and dynamical behaviors of multiple equilibrium points for neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays. The fixed point theorem and other analytical tools are used to develop certain sufficient conditions that ensure that the n-dimensional discontinuous neural networks with time-varying delays can have at least 5(n) equilibrium points, 3(n) of which are locally stable and the others are unstable. The importance of the derived results is that it reveals that the discontinuous neural networks can have greater storage capacity than the continuous ones. Moreover, different from the existing results on multistability of neural networks with discontinuous activation functions, the 3(n) locally stable equilibrium points obtained in this paper are located in not only saturated regions, but also unsaturated regions, due to the non-monotonic structure of discontinuous activation functions. A numerical simulation study is conducted to illustrate and support the derived theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Non-monotonicity and divergent time scale in Axelrod model dynamics

Science.gov (United States)

Vazquez, F.; Redner, S.

2007-04-01

We study the evolution of the Axelrod model for cultural diversity, a prototypical non-equilibrium process that exhibits rich dynamics and a dynamic phase transition between diversity and an inactive state. We consider a simple version of the model in which each individual possesses two features that can assume q possibilities. Within a mean-field description in which each individual has just a few interaction partners, we find a phase transition at a critical value qc between an active, diverse state for q < qc and a frozen state. For q lesssim qc, the density of active links is non-monotonic in time and the asymptotic approach to the steady state is controlled by a time scale that diverges as (q-qc)-1/2.

Non-Monotonic Survival of Staphylococcus aureus with Respect to Ciprofloxacin Concentration Arises from Prophage-Dependent Killing of Persisters

Directory of Open Access Journals (Sweden)

Elizabeth L. Sandvik

2015-11-01

Full Text Available Staphylococcus aureus is a notorious pathogen with a propensity to cause chronic, non-healing wounds. Bacterial persisters have been implicated in the recalcitrance of S. aureus infections, and this motivated us to examine the persistence of S. aureus to ciprofloxacin, a quinolone antibiotic. Upon treatment of exponential phase S. aureus with ciprofloxacin, we observed that survival was a non-monotonic function of ciprofloxacin concentration. Maximal killing occurred at 1 µg/mL ciprofloxacin, which corresponded to survival that was up to ~40-fold lower than that obtained with concentrations ≥ 5 µg/mL. Investigation of this phenomenon revealed that the non-monotonic response was associated with prophage induction, which facilitated killing of S. aureus persisters. Elimination of prophage induction with tetracycline was found to prevent cell lysis and persister killing. We anticipate that these findings may be useful for the design of quinolone treatments.

A Binomial Modeling Approach for Upscaling Colloid Transport Under Unfavorable Attachment Conditions: Emergent Prediction of Nonmonotonic Retention Profiles

Science.gov (United States)

Hilpert, Markus; Johnson, William P.

2018-01-01

We used a recently developed simple mathematical network model to upscale pore-scale colloid transport information determined under unfavorable attachment conditions. Classical log-linear and nonmonotonic retention profiles, both well-reported under favorable and unfavorable attachment conditions, respectively, emerged from our upscaling. The primary attribute of the network is colloid transfer between bulk pore fluid, the near-surface fluid domain (NSFD), and attachment (treated as irreversible). The network model accounts for colloid transfer to the NSFD of downgradient grains and for reentrainment to bulk pore fluid via diffusion or via expulsion at rear flow stagnation zones (RFSZs). The model describes colloid transport by a sequence of random trials in a one-dimensional (1-D) network of Happel cells, which contain a grain and a pore. Using combinatorial analysis that capitalizes on the binomial coefficient, we derived from the pore-scale information the theoretical residence time distribution of colloids in the network. The transition from log-linear to nonmonotonic retention profiles occurs when the conditions underlying classical filtration theory are not fulfilled, i.e., when an NSFD colloid population is maintained. Then, nonmonotonic retention profiles result potentially both for attached and NSFD colloids. The concentration maxima shift downgradient depending on specific parameter choice. The concentration maxima were also shown to shift downgradient temporally (with continued elution) under conditions where attachment is negligible, explaining experimentally observed downgradient transport of retained concentration maxima of adhesion-deficient bacteria. For the case of zero reentrainment, we develop closed-form, analytical expressions for the shape, and the maximum of the colloid retention profile.

Internal m=1, n=1 helical mode in a tokamak with nonmonotonic current profile

International Nuclear Information System (INIS)

Kuvshinov, B.N.; Mikhajlovskij, A.B.

1988-01-01

Internal helical mode in a tokamak with two resonance surfaces, on which storing coefficient reduces to unity is studied theoretically. A general criterion for the investigated perturbations stability is obtained. Dispersion equation, describing both ideal and resistive helical modes, is derived. Analytic calculations for the case of perturbations localized near the tokamak axis are made. It is shown that in the framework of standard ideal hydrodynamics such perturbations are unstable at characteristic nonmonotonous profiles of the current

Restricted Variance Interaction Effects

DEFF Research Database (Denmark)

Cortina, Jose M.; Köhler, Tine; Keeler, Kathleen R.

2018-01-01

Although interaction hypotheses are increasingly common in our field, many recent articles point out that authors often have difficulty justifying them. The purpose of this article is to describe a particular type of interaction: the restricted variance (RV) interaction. The essence of the RV int...

Multistability of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays.

Science.gov (United States)

Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

2015-11-01

The problem of coexistence and dynamical behaviors of multiple equilibrium points is addressed for a class of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays. By virtue of the fixed point theorem, nonsmooth analysis theory and other analytical tools, some sufficient conditions are established to guarantee that such n-dimensional memristive Cohen-Grossberg neural networks can have 5(n) equilibrium points, among which 3(n) equilibrium points are locally exponentially stable. It is shown that greater storage capacity can be achieved by neural networks with the non-monotonic activation functions introduced herein than the ones with Mexican-hat-type activation function. In addition, unlike most existing multistability results of neural networks with monotonic activation functions, those obtained 3(n) locally stable equilibrium points are located both in saturated regions and unsaturated regions. The theoretical findings are verified by an illustrative example with computer simulations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Beyond the Mean: Sensitivities of the Variance of Population Growth.

Science.gov (United States)

Trotter, Meredith V; Krishna-Kumar, Siddharth; Tuljapurkar, Shripad

2013-03-01

Populations in variable environments are described by both a mean growth rate and a variance of stochastic population growth. Increasing variance will increase the width of confidence bounds around estimates of population size, growth, probability of and time to quasi-extinction. However, traditional sensitivity analyses of stochastic matrix models only consider the sensitivity of the mean growth rate. We derive an exact method for calculating the sensitivity of the variance in population growth to changes in demographic parameters. Sensitivities of the variance also allow a new sensitivity calculation for the cumulative probability of quasi-extinction. We apply this new analysis tool to an empirical dataset on at-risk polar bears to demonstrate its utility in conservation biology We find that in many cases a change in life history parameters will increase both the mean and variance of population growth of polar bears. This counterintuitive behaviour of the variance complicates predictions about overall population impacts of management interventions. Sensitivity calculations for cumulative extinction risk factor in changes to both mean and variance, providing a highly useful quantitative tool for conservation management. The mean stochastic growth rate and its sensitivities do not fully describe the dynamics of population growth. The use of variance sensitivities gives a more complete understanding of population dynamics and facilitates the calculation of new sensitivities for extinction processes.

Environmentally-relevant concentrations of atrazine induce non-monotonic acceleration of developmental rate and increased size at metamorphosis in Rhinella arenarum tadpoles.

Science.gov (United States)

Brodeur, Julie C; Sassone, Alina; Hermida, Gladys N; Codugnello, Nadia

2013-06-01

Despite of the various studies reporting on the subject, anticipating the impacts of the widely-used herbicide atrazine on anuran tadpoles metamorphosis remains complex as increases or decreases of larval period duration are almost as frequently reported as an absence of effect. The aim of the present study was to examine the effects of environmentally-relevant concentrations of atrazine (0.1, 1, 10, 100, and 1000μg/L) on the timings of metamorphosis and body size at metamorphosis in the common South American toad, Rhinella arenarum (Anura: bufonidae). None of the atrazine concentrations tested significantly altered survival. Low atrazine concentrations in the range of 1-100μg/L were found to accelerate developmental rate in a non-monotonic U-shaped concentration-response relationship. This observed acceleration of the metamorphic process occurred entirely between stages 25 and 39; treated tadpoles proceeding through metamorphosis as control animals beyond this point. Together with proceeding through metamorphosis at a faster rate, tadpoles exposed to atrazine concentrations in the range of 1-100μg/L furthermore transformed into significantly larger metamorphs than controls, the concentration-response curve taking the form of an inverted U in this case. The no observed effect concentration (NOEC) was 0.1μg atrazine/L for both size at metamorphosis and timings of metamorphosis. Tadpoles exposed to 100μg/L 17β-estradiol presented the exact same alterations of developmental rate and body size as those treated with 1, 10 and 100μg/L of atrazine. Elements of the experimental design that facilitated the detection of alterations of metamorphosis at low concentrations of atrazine are discussed, together with the ecological significance of those findings. Copyright © 2013 Elsevier Inc. All rights reserved.

Non-monotonic piezoresistive behaviour of graphene nanoplatelet (GNP-polymer composite flexible films prepared by solvent casting

Directory of Open Access Journals (Sweden)

S. Makireddi

2017-07-01

Full Text Available Graphene-polymer nanocomposite films show good piezoresistive behaviour and it is reported that the sensitivity increases either with the increased sheet resistance or decreased number density of the graphene fillers. A little is known about this behaviour near the percolation region. In this study, graphene nanoplatelet (GNP/poly (methyl methacrylate (PMMA flexible films are fabricated via solution casting process at varying weight percent of GNP. Electrical and piezoresistive behaviour of these films is studied as a function of GNP concentration. Piezoresistive strain sensitivity of the films is measured by affixing the film to an aluminium specimen which is subjected to monotonic uniaxial tensile load. The change in resistance of the film with strain is monitored using a four probe. An electrical percolation threshold at 3 weight percent of GNP is observed. We report non-monotonic piezoresistive behaviour of these films as a function GNP concentration. We observe an increase in gauge factor (GF with unstrained resistance of the films up to a critical resistance corresponding to percolation threshold. Beyond this limit the GF decreases with unstrained resistance.

Raman D-band in the irradiated graphene: Origin of the non-monotonous dependence of its intensity with defect concentration

International Nuclear Information System (INIS)

Codorniu Pujals, Daniel

2013-01-01

Raman spectroscopy is one of the most used experimental techniques in studying irradiated carbon nanostructures, in particular graphene, due to its high sensibility to the presence of defects in the crystalline lattice. Special attention has been given to the variation of the intensity of the Raman D-band of graphene with the concentration of defects produced by irradiation. Nowadays, there are enough experimental evidences about the non-monotonous character of that dependence, but the explanation of this behavior is still controversial. In the present work we developed a simplified mathematical model to obtain a functional relationship between these two magnitudes and showed that the non-monotonous dependence is intrinsic to the nature of the D-band and that it is not necessarily linked to amorphization processes. The obtained functional dependence was used to fit experimental data taken from other authors. The determination coefficient of the fitting was 0.96.

Downside Variance Risk Premium

OpenAIRE

Feunou, Bruno; Jahan-Parvar, Mohammad; Okou, Cedric

2015-01-01

We propose a new decomposition of the variance risk premium in terms of upside and downside variance risk premia. The difference between upside and downside variance risk premia is a measure of skewness risk premium. We establish that the downside variance risk premium is the main component of the variance risk premium, and that the skewness risk premium is a priced factor with significant prediction power for aggregate excess returns. Our empirical investigation highlights the positive and s...

Low dose effects and non-monotonic dose responses for endocrine active chemicals: Science to practice workshop: Workshop summary

DEFF Research Database (Denmark)

Beausoleil, Claire; Ormsby, Jean-Nicolas; Gies, Andreas

2013-01-01

A workshop was held in Berlin September 12–14th 2012 to assess the state of the science of the data supporting low dose effects and non-monotonic dose responses (“low dose hypothesis”) for chemicals with endocrine activity (endocrine disrupting chemicals or EDCs). This workshop consisted of lectu...

Non-monotonic dose dependence of the Ge- and Ti-centres in quartz

International Nuclear Information System (INIS)

Woda, C.; Wagner, G.A.

2007-01-01

The dose response of the Ge- and Ti-centres in quartz is studied over a large dose range. After an initial signal increase in the low dose range, both defects show a pronounced decrease in signal intensities for high doses. The model by Euler and Kahan [1987. Radiation effects and anelastic loss in germanium-doped quartz. Phys. Rev. B 35 (9), 4351-4359], in which the signal drop is explained by an enhanced trapping of holes at the electron trapping site, is critically discussed. A generalization of the model is then developed, following similar considerations by Lawless et al. [2005. A model for non-monotonic dose dependence of thermoluminescence (TL). J. Phys. Condens. Matter 17, 737-753], who explained a signal drop in TL by an enhanced recombination rate with electrons at the recombination centre. Finally, an alternative model for the signal decay is given, based on the competition between single and double electron capture at the electron trapping site. From the critical discussion of the different models it is concluded that the double electron capture mechanism is the most probable effect for the dose response

R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization.

Science.gov (United States)

Dazard, Jean-Eudes; Xu, Hua; Rao, J Sunil

2011-01-01

We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets ( p ≫ n paradigm), such as in 'omics'-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real 'omics' test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR ('Mean-Variance Regularization'), downloadable from the CRAN.

Estimation of measurement variances

International Nuclear Information System (INIS)

Anon.

1981-01-01

In the previous two sessions, it was assumed that the measurement error variances were known quantities when the variances of the safeguards indices were calculated. These known quantities are actually estimates based on historical data and on data generated by the measurement program. Session 34 discusses how measurement error parameters are estimated for different situations. The various error types are considered. The purpose of the session is to enable participants to: (1) estimate systematic error variances from standard data; (2) estimate random error variances from data as replicate measurement data; (3) perform a simple analysis of variances to characterize the measurement error structure when biases vary over time

Simulation study on heterogeneous variance adjustment for observations with different measurement error variance

DEFF Research Database (Denmark)

Pitkänen, Timo; Mäntysaari, Esa A; Nielsen, Ulrik Sander

2013-01-01

of variance correction is developed for the same observations. As automated milking systems are becoming more popular the current evaluation model needs to be enhanced to account for the different measurement error variances of observations from automated milking systems. In this simulation study different...... models and different approaches to account for heterogeneous variance when observations have different measurement error variances were investigated. Based on the results we propose to upgrade the currently applied models and to calibrate the heterogeneous variance adjustment method to yield same genetic......The Nordic Holstein yield evaluation model describes all available milk, protein and fat test-day yields from Denmark, Finland and Sweden. In its current form all variance components are estimated from observations recorded under conventional milking systems. Also the model for heterogeneity...

Why risk is not variance: an expository note.

Science.gov (United States)

Cox, Louis Anthony Tony

2008-08-01

Variance (or standard deviation) of return is widely used as a measure of risk in financial investment risk analysis applications, where mean-variance analysis is applied to calculate efficient frontiers and undominated portfolios. Why, then, do health, safety, and environmental (HS&E) and reliability engineering risk analysts insist on defining risk more flexibly, as being determined by probabilities and consequences, rather than simply by variances? This note suggests an answer by providing a simple proof that mean-variance decision making violates the principle that a rational decisionmaker should prefer higher to lower probabilities of receiving a fixed gain, all else being equal. Indeed, simply hypothesizing a continuous increasing indifference curve for mean-variance combinations at the origin is enough to imply that a decisionmaker must find unacceptable some prospects that offer a positive probability of gain and zero probability of loss. Unlike some previous analyses of limitations of variance as a risk metric, this expository note uses only simple mathematics and does not require the additional framework of von Neumann Morgenstern utility theory.

A COSMIC VARIANCE COOKBOOK

International Nuclear Information System (INIS)

Moster, Benjamin P.; Rix, Hans-Walter; Somerville, Rachel S.; Newman, Jeffrey A.

2011-01-01

Deep pencil beam surveys ( 2 ) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by 'cosmic variance'. This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift z-bar and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, z-bar , Δz, and stellar mass m * . We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at z-bar =2 and with Δz = 0.5, the relative cosmic variance of galaxies with m * >10 11 M sun is ∼38%, while it is ∼27% for GEMS and ∼12% for COSMOS. For galaxies of m * ∼ 10 10 M sun , the relative cosmic variance is ∼19% for GOODS, ∼13% for GEMS, and ∼6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at z-bar =2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic

Multistability and gluing bifurcation to butterflies in coupled networks with non-monotonic feedback

International Nuclear Information System (INIS)

Ma Jianfu; Wu Jianhong

2009-01-01

Neural networks with a non-monotonic activation function have been proposed to increase their capacity for memory storage and retrieval, but there is still a lack of rigorous mathematical analysis and detailed discussions of the impact of time lag. Here we consider a two-neuron recurrent network. We first show how supercritical pitchfork bifurcations and a saddle-node bifurcation lead to the coexistence of multiple stable equilibria (multistability) in the instantaneous updating network. We then study the effect of time delay on the local stability of these equilibria and show that four equilibria lose their stability at a certain critical value of time delay, and Hopf bifurcations of these equilibria occur simultaneously, leading to multiple coexisting periodic orbits. We apply centre manifold theory and normal form theory to determine the direction of these Hopf bifurcations and the stability of bifurcated periodic orbits. Numerical simulations show very interesting global patterns of periodic solutions as the time delay is varied. In particular, we observe that these four periodic solutions are glued together along the stable and unstable manifolds of saddle points to develop a butterfly structure through a complicated process of gluing bifurcations of periodic solutions

Quantitative non-monotonic modeling of economic uncertainty by probability and possibility distributions

DEFF Research Database (Denmark)

Schjær-Jacobsen, Hans

2012-01-01

uncertainty can be calculated. The possibility approach is particular well suited for representation of uncertainty of a non-statistical nature due to lack of knowledge and requires less information than the probability approach. Based on the kind of uncertainty and knowledge present, these aspects...... to the understanding of similarities and differences of the two approaches as well as practical applications. The probability approach offers a good framework for representation of randomness and variability. Once the probability distributions of uncertain parameters and their correlations are known the resulting...... are thoroughly discussed in the case of rectangular representation of uncertainty by the uniform probability distribution and the interval, respectively. Also triangular representations are dealt with and compared. Calculation of monotonic as well as non-monotonic functions of variables represented...

MCNP variance reduction overview

International Nuclear Information System (INIS)

Hendricks, J.S.; Booth, T.E.

1985-01-01

The MCNP code is rich in variance reduction features. Standard variance reduction methods found in most Monte Carlo codes are available as well as a number of methods unique to MCNP. We discuss the variance reduction features presently in MCNP as well as new ones under study for possible inclusion in future versions of the code

Spectral Ambiguity of Allan Variance

Science.gov (United States)

Greenhall, C. A.

1996-01-01

We study the extent to which knowledge of Allan variance and other finite-difference variances determines the spectrum of a random process. The variance of first differences is known to determine the spectrum. We show that, in general, the Allan variance does not. A complete description of the ambiguity is given.

Variance bias analysis for the Gelbard's batch method

Energy Technology Data Exchange (ETDEWEB)

Seo, Jae Uk; Shim, Hyung Jin [Seoul National Univ., Seoul (Korea, Republic of)

2014-05-15

In this paper, variances and the bias will be derived analytically when the Gelbard's batch method is applied. And then, the real variance estimated from this bias will be compared with the real variance calculated from replicas. Variance and the bias were derived analytically when the batch method was applied. If the batch method was applied to calculate the sample variance, covariance terms between tallies which exist in the batch were eliminated from the bias. With the 2 by 2 fission matrix problem, we could calculate real variance regardless of whether or not the batch method was applied. However as batch size got larger, standard deviation of real variance was increased. When we perform a Monte Carlo estimation, we could get a sample variance as the statistical uncertainty of it. However, this value is smaller than the real variance of it because a sample variance is biased. To reduce this bias, Gelbard devised the method which is called the Gelbard's batch method. It has been certificated that a sample variance get closer to the real variance when the batch method is applied. In other words, the bias get reduced. This fact is well known to everyone in the MC field. However, so far, no one has given the analytical interpretation on it.

Demonstration of a zero-variance based scheme for variance reduction to a mini-core Monte Carlo calculation

Energy Technology Data Exchange (ETDEWEB)

Christoforou, Stavros, E-mail: stavros.christoforou@gmail.com [Kirinthou 17, 34100, Chalkida (Greece); Hoogenboom, J. Eduard, E-mail: j.e.hoogenboom@tudelft.nl [Department of Applied Sciences, Delft University of Technology (Netherlands)

2011-07-01

A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k{sub eff} estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)

Permanence of a Semi-Ratio-Dependent Predator-Prey System with Nonmonotonic Functional Response and Time Delay

Directory of Open Access Journals (Sweden)

Xuepeng Li

2009-01-01

Full Text Available Sufficient conditions for permanence of a semi-ratio-dependent predator-prey system with nonmonotonic functional response and time delay ̇1(=1([1(−11(1(−(−12(2(/(2+21(],  ̇2(=2([2(−21(2(/1(], are obtained, where 1( and 2( stand for the density of the prey and the predator, respectively, and ≠0 is a constant. (≥0 stands for the time delays due to negative feedback of the prey population.

Condition-based inspection/replacement policies for non-monotone deteriorating systems with environmental covariates

Energy Technology Data Exchange (ETDEWEB)

Zhao Xuejing [Universite de Technologie de Troyes, Institut Charles Delaunay and STMR UMR CNRS 6279, 12 rue Marie Curie, 10010 Troyes (France); School of mathematics and statistics, Lanzhou University, Lanzhou 730000 (China); Fouladirad, Mitra, E-mail: mitra.fouladirad@utt.f [Universite de Technologie de Troyes, Institut Charles Delaunay and STMR UMR CNRS 6279, 12 rue Marie Curie, 10010 Troyes (France); Berenguer, Christophe [Universite de Technologie de Troyes, Institut Charles Delaunay and STMR UMR CNRS 6279, 12 rue Marie Curie, 10010 Troyes (France); Bordes, Laurent [Universite de Pau et des Pays de l' Adour, LMA UMR CNRS 5142, 64013 PAU Cedex (France)

2010-08-15

The aim of this paper is to discuss the problem of modelling and optimising condition-based maintenance policies for a deteriorating system in presence of covariates. The deterioration is modelled by a non-monotone stochastic process. The covariates process is assumed to be a time-homogenous Markov chain with finite state space. A model similar to the proportional hazards model is used to show the influence of covariates on the deterioration. In the framework of the system under consideration, an appropriate inspection/replacement policy which minimises the expected average maintenance cost is derived. The average cost under different conditions of covariates and different maintenance policies is analysed through simulation experiments to compare the policies performances.

Condition-based inspection/replacement policies for non-monotone deteriorating systems with environmental covariates

International Nuclear Information System (INIS)

Zhao Xuejing; Fouladirad, Mitra; Berenguer, Christophe; Bordes, Laurent

2010-01-01

The aim of this paper is to discuss the problem of modelling and optimising condition-based maintenance policies for a deteriorating system in presence of covariates. The deterioration is modelled by a non-monotone stochastic process. The covariates process is assumed to be a time-homogenous Markov chain with finite state space. A model similar to the proportional hazards model is used to show the influence of covariates on the deterioration. In the framework of the system under consideration, an appropriate inspection/replacement policy which minimises the expected average maintenance cost is derived. The average cost under different conditions of covariates and different maintenance policies is analysed through simulation experiments to compare the policies performances.

Origin and consequences of the relationship between protein mean and variance.

Science.gov (United States)

Vallania, Francesco Luigi Massimo; Sherman, Marc; Goodwin, Zane; Mogno, Ilaria; Cohen, Barak Alon; Mitra, Robi David

2014-01-01

Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝μ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝μ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome.

Variance analysis of forecasted streamflow maxima in a wet temperate climate

Science.gov (United States)

Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

2018-05-01

Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

Demonstration of a zero-variance based scheme for variance reduction to a mini-core Monte Carlo calculation

International Nuclear Information System (INIS)

Christoforou, Stavros; Hoogenboom, J. Eduard

2011-01-01

A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k_e_f_f estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)

Continuous-Time Mean-Variance Portfolio Selection under the CEV Process

Directory of Open Access Journals (Sweden)

Hui-qiang Ma

2014-01-01

Full Text Available We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance efficient frontier analytically. The results show that the mean-variance efficient frontier is still a parabola in the mean-variance plane, and the optimal strategies depend not only on the total wealth but also on the stock price. Moreover, some numerical examples are given to analyze the sensitivity of the efficient frontier with respect to the elasticity parameter and to illustrate the results presented in this paper. The numerical results show that the price of risk decreases as the elasticity coefficient increases.

Dominance genetic variance for traits under directional selection in Drosophila serrata.

Science.gov (United States)

Sztepanacz, Jacqueline L; Blows, Mark W

2015-05-01

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. Copyright © 2015 by the Genetics Society of America.

CMB-S4 and the hemispherical variance anomaly

Science.gov (United States)

O'Dwyer, Márcio; Copi, Craig J.; Knox, Lloyd; Starkman, Glenn D.

2017-09-01

Cosmic microwave background (CMB) full-sky temperature data show a hemispherical asymmetry in power nearly aligned with the Ecliptic. In real space, this anomaly can be quantified by the temperature variance in the Northern and Southern Ecliptic hemispheres, with the Northern hemisphere displaying an anomalously low variance while the Southern hemisphere appears unremarkable [consistent with expectations from the best-fitting theory, Lambda Cold Dark Matter (ΛCDM)]. While this is a well-established result in temperature, the low signal-to-noise ratio in current polarization data prevents a similar comparison. This will change with a proposed ground-based CMB experiment, CMB-S4. With that in mind, we generate realizations of polarization maps constrained by the temperature data and predict the distribution of the hemispherical variance in polarization considering two different sky coverage scenarios possible in CMB-S4: full Ecliptic north coverage and just the portion of the North that can be observed from a ground-based telescope at the high Chilean Atacama plateau. We find that even in the set of realizations constrained by the temperature data, the low Northern hemisphere variance observed in temperature is not expected in polarization. Therefore, observing an anomalously low variance in polarization would make the hypothesis that the temperature anomaly is simply a statistical fluke more unlikely and thus increase the motivation for physical explanations. We show, within ΛCDM, how variance measurements in both sky coverage scenarios are related. We find that the variance makes for a good statistic in cases where the sky coverage is limited, however, full northern coverage is still preferable.

Assessing dose-response relationships for endocrine disrupting chemicals (EDCs): a focus on non-monotonicity.

Science.gov (United States)

Zoeller, R Thomas; Vandenberg, Laura N

2015-05-15

The fundamental principle in regulatory toxicology is that all chemicals are toxic and that the severity of effect is proportional to the exposure level. An ancillary assumption is that there are no effects at exposures below the lowest observed adverse effect level (LOAEL), either because no effects exist or because they are not statistically resolvable, implying that they would not be adverse. Chemicals that interfere with hormones violate these principles in two important ways: dose-response relationships can be non-monotonic, which have been reported in hundreds of studies of endocrine disrupting chemicals (EDCs); and effects are often observed below the LOAEL, including all environmental epidemiological studies examining EDCs. In recognition of the importance of this issue, Lagarde et al. have published the first proposal to qualitatively assess non-monotonic dose response (NMDR) relationships for use in risk assessments. Their proposal represents a significant step forward in the evaluation of complex datasets for use in risk assessments. Here, we comment on three elements of the Lagarde proposal that we feel need to be assessed more critically and present our arguments: 1) the use of Klimisch scores to evaluate study quality, 2) the concept of evaluating study quality without topical experts' knowledge and opinions, and 3) the requirement of establishing the biological plausibility of an NMDR before consideration for use in risk assessment. We present evidence-based logical arguments that 1) the use of the Klimisch score should be abandoned for assessing study quality; 2) evaluating study quality requires experts in the specific field; and 3) an understanding of mechanisms should not be required to accept observable, statistically valid phenomena. It is our hope to contribute to the important and ongoing debate about the impact of NMDRs on risk assessment with positive suggestions.

Allowing variance may enlarge the safe operating space for exploited ecosystems.

Science.gov (United States)

Carpenter, Stephen R; Brock, William A; Folke, Carl; van Nes, Egbert H; Scheffer, Marten

2015-11-17

Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictability may therefore be preferred. However, actions to decrease variance over short timescales (2-4 y), when applied continuously, may lead to long-term ecosystem changes with adverse consequences. We investigated the effects of managing short-term variance in three well-understood models of ecosystem services: lake eutrophication, harvest of a wild population, and yield of domestic herbivores on a rangeland. In all cases, actions to decrease variance can increase the risk of crossing critical ecosystem thresholds, resulting in less desirable ecosystem states. Managing to decrease short-term variance creates ecosystem fragility by changing the boundaries of safe operating spaces, suppressing information needed for adaptive management, cancelling signals of declining resilience, and removing pressures that may build tolerance of stress. Thus, the management of variance interacts strongly and inseparably with the management of resilience. By allowing for variation, learning, and flexibility while observing change, managers can detect opportunities and problems as they develop while sustaining the capacity to deal with them.

Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium

DEFF Research Database (Denmark)

Casas, Isabel; Mao, Xiuping; Veiga, Helena

This study explores the predictive power of new estimators of the equity variance risk premium and conditional variance for future excess stock market returns, economic activity, and financial instability, both during and after the last global financial crisis. These estimators are obtained from...... time-varying coefficient models are the ones showing considerably higher predictive power for stock market returns and financial instability during the financial crisis, suggesting that an extreme volatility period requires models that can adapt quickly to turmoil........ Moreover, a comparison of the overall results reveals that the conditional variance gains predictive power during the global financial crisis period. Furthermore, both the variance risk premium and conditional variance are determined to be predictors of future financial instability, whereas conditional...

Variance estimation in the analysis of microarray data

KAUST Repository

Wang, Yuedong

2009-04-01

Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

Non-Monotonic Relation Between Noise Exposure Severity and Neuronal Hyperactivity in the Auditory Midbrain

Directory of Open Access Journals (Sweden)

Lara Li Hesse

2016-08-01

Full Text Available The occurrence of tinnitus can be linked to hearing loss in the majority of cases, but there is nevertheless a large degree of unexplained heterogeneity in the relation between hearing loss and tinnitus. Part of the problem might be that hearing loss is usually quantified in terms of increased hearing thresholds, which only provides limited information about the underlying cochlear damage. Moreover, noise exposure that does not cause hearing threshold loss can still lead to hidden hearing loss (HHL, i.e. functional deafferentation of auditory nerve fibres (ANFs through loss of synaptic ribbons in inner hair cells. Whilst it is known that increased hearing thresholds can trigger increases in spontaneous neural activity in the central auditory system, i.e. a putative neural correlate of tinnitus, the central effects of HHL have not yet been investigated. Here, we exposed mice to octave-band noise at 100 and 105 dB SPL, to generate HHL and permanent increases of hearing thresholds, respectively. Deafferentation of ANFs was confirmed through measurement of auditory brainstem responses and cochlear immunohistochemistry. Acute extracellular recordings from the auditory midbrain (inferior colliculus demonstrated increases in spontaneous neuronal activity (a putative neural correlate of tinnitus in both groups. Surprisingly the increase in spontaneous activity was most pronounced in the mice with HHL, suggesting that the relation between hearing loss and neuronal hyperactivity might be more complex than currently understood. Our computational model indicated that these differences in neuronal hyperactivity could arise from different degrees of deafferentation of low-threshold ANFs in the two exposure groups.Our results demonstrate that HHL is sufficient to induce changes in central auditory processing, and they also indicate a non-monotonic relationship between cochlear damage and neuronal hyperactivity, suggesting an explanation for why tinnitus might

Effect of sequence variants on variance in glucose levels predicts type 2 diabetes risk and accounts for heritability.

Science.gov (United States)

Ivarsdottir, Erna V; Steinthorsdottir, Valgerdur; Daneshpour, Maryam S; Thorleifsson, Gudmar; Sulem, Patrick; Holm, Hilma; Sigurdsson, Snaevar; Hreidarsson, Astradur B; Sigurdsson, Gunnar; Bjarnason, Ragnar; Thorsson, Arni V; Benediktsson, Rafn; Eyjolfsson, Gudmundur; Sigurdardottir, Olof; Olafsson, Isleifur; Zeinali, Sirous; Azizi, Fereidoun; Thorsteinsdottir, Unnur; Gudbjartsson, Daniel F; Stefansson, Kari

2017-09-01

Sequence variants that affect mean fasting glucose levels do not necessarily affect risk for type 2 diabetes (T2D). We assessed the effects of 36 reported glucose-associated sequence variants on between- and within-subject variance in fasting glucose levels in 69,142 Icelanders. The variant in TCF7L2 that increases fasting glucose levels increases between-subject variance (5.7% per allele, P = 4.2 × 10 -10 ), whereas variants in GCK and G6PC2 that increase fasting glucose levels decrease between-subject variance (7.5% per allele, P = 4.9 × 10 -11 and 7.3% per allele, P = 7.5 × 10 -18 , respectively). Variants that increase mean and between-subject variance in fasting glucose levels tend to increase T2D risk, whereas those that increase the mean but reduce variance do not (r 2 = 0.61). The variants that increase between-subject variance increase fasting glucose heritability estimates. Intuitively, our results show that increasing the mean and variance of glucose levels is more likely to cause pathologically high glucose levels than increase in the mean offset by a decrease in variance.

Assessment of ulnar variance: a radiological investigation in a Dutch population

Energy Technology Data Exchange (ETDEWEB)

Schuurman, A.H. [Dept. of Plastic, Reconstructive and Hand Surgery, University Medical Centre, Utrecht (Netherlands); Dept. of Plastic Surgery, University Medical Centre, Utrecht (Netherlands); Maas, M.; Dijkstra, P.F. [Dept. of Radiology, Univ. of Amsterdam (Netherlands); Kauer, J.M.G. [Dept. of Anatomy and Embryology, Univ. of Nijmegen (Netherlands)

2001-11-01

Objective: A radiological study was performed to evaluate ulnar variance in 68 Dutch patients using an electronic digitizer compared with Palmer's concentric circle method. Using the digitizer method only, the effect of different wrist positions and grip on ulnar variance was then investigated. Finally the distribution of ulnar variance in the selected patients was investigated also using the digitizer method. Design and patients: All radiographs were performed with the wrist in a standard zero-rotation position (posteroanterior) and in supination (anteroposterior). Palmer's concentric circle method and an electronic digitizer connected to a personal computer were used to measure ulnar variance. The digitizer consists of a Plexiglas plate with an electronically activated grid beneath it. A radiograph is placed on the plate and a cursor activates a point on the grid. Three plots are marked on the radius and one plot on the most distal part of the ulnar head. The digitizer then determines the difference between a radius passing through the radius plots and the ulnar plot. Results and conclusions: Using the concentric circle method we found an ulna plus predominance, but an ulna minus predominance when using the digitizer method. Overall the ulnar variance distribution for Palmer's method was 41.9% ulna plus, 25.7% neutral and 32.4% ulna minus variance, and for the digitizer method was 40.4% ulna plus, 1.5% neutral and 58.1% ulna minus. The percentage ulnar variance greater than 1 mm on standard radiographs increased from 23% to 58% using the digitizer, with maximum grip, clearly demonstrating the (dynamic) effect of grip on ulnar variance. This almost threefold increase was found to be a significant difference. Significant differences were found between ulnar variance when different wrist positions were compared. (orig.)

Approximate zero-variance Monte Carlo estimation of Markovian unreliability

International Nuclear Information System (INIS)

Delcoux, J.L.; Labeau, P.E.; Devooght, J.

1997-01-01

Monte Carlo simulation has become an important tool for the estimation of reliability characteristics, since conventional numerical methods are no more efficient when the size of the system to solve increases. However, evaluating by a simulation the probability of occurrence of very rare events means playing a very large number of histories of the system, which leads to unacceptable computation times. Acceleration and variance reduction techniques have to be worked out. We show in this paper how to write the equations of Markovian reliability as a transport problem, and how the well known zero-variance scheme can be adapted to this application. But such a method is always specific to the estimation of one quality, while a Monte Carlo simulation allows to perform simultaneously estimations of diverse quantities. Therefore, the estimation of one of them could be made more accurate while degrading at the same time the variance of other estimations. We propound here a method to reduce simultaneously the variance for several quantities, by using probability laws that would lead to zero-variance in the estimation of a mean of these quantities. Just like the zero-variance one, the method we propound is impossible to perform exactly. However, we show that simple approximations of it may be very efficient. (author)

Genetic control of residual variance of yearling weight in Nellore beef cattle.

Science.gov (United States)

Iung, L H S; Neves, H H R; Mulder, H A; Carvalheiro, R

2017-04-01

There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 ± 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (Box-Cox transformation was able to decrease the dependence of the variance on the mean and decreased the estimates of genetic parameters for residual variance. The transformation reduced but did not eliminate all the genetic heterogeneity of residual variance, highlighting

Variance Reduction Techniques in Monte Carlo Methods

NARCIS (Netherlands)

Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.

2010-01-01

Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the

Portfolio optimization using median-variance approach

Science.gov (United States)

Wan Mohd, Wan Rosanisah; Mohamad, Daud; Mohamed, Zulkifli

2013-04-01

Optimization models have been applied in many decision-making problems particularly in portfolio selection. Since the introduction of Markowitz's theory of portfolio selection, various approaches based on mathematical programming have been introduced such as mean-variance, mean-absolute deviation, mean-variance-skewness and conditional value-at-risk (CVaR) mainly to maximize return and minimize risk. However most of the approaches assume that the distribution of data is normal and this is not generally true. As an alternative, in this paper, we employ the median-variance approach to improve the portfolio optimization. This approach has successfully catered both types of normal and non-normal distribution of data. With this actual representation, we analyze and compare the rate of return and risk between the mean-variance and the median-variance based portfolio which consist of 30 stocks from Bursa Malaysia. The results in this study show that the median-variance approach is capable to produce a lower risk for each return earning as compared to the mean-variance approach.

Efficient Cardinality/Mean-Variance Portfolios

OpenAIRE

Brito, R. Pedro; Vicente, Luís Nunes

2014-01-01

International audience; We propose a novel approach to handle cardinality in portfolio selection, by means of a biobjective cardinality/mean-variance problem, allowing the investor to analyze the efficient tradeoff between return-risk and number of active positions. Recent progress in multiobjective optimization without derivatives allow us to robustly compute (in-sample) the whole cardinality/mean-variance efficient frontier, for a variety of data sets and mean-variance models. Our results s...

Biological Variance in Agricultural Products. Theoretical Considerations

NARCIS (Netherlands)

Tijskens, L.M.M.; Konopacki, P.

2003-01-01

The food that we eat is uniform neither in shape or appearance nor in internal composition or content. Since technology became increasingly important, the presence of biological variance in our food became more and more of a nuisance. Techniques and procedures (statistical, technical) were

Non-monotonic spatial distribution of the interstellar dust in astrospheres: finite gyroradius effect

Science.gov (United States)

Katushkina, O. A.; Alexashov, D. B.; Izmodenov, V. V.; Gvaramadze, V. V.

2017-02-01

High-resolution mid-infrared observations of astrospheres show that many of them have filamentary (cirrus-like) structure. Using numerical models of dust dynamics in astrospheres, we suggest that their filamentary structure might be related to specific spatial distribution of the interstellar dust around the stars, caused by a gyrorotation of charged dust grains in the interstellar magnetic field. Our numerical model describes the dust dynamics in astrospheres under an influence of the Lorentz force and assumption of a constant dust charge. Calculations are performed for the dust grains with different sizes separately. It is shown that non-monotonic spatial dust distribution (viewed as filaments) appears for dust grains with the period of gyromotion comparable with the characteristic time-scale of the dust motion in the astrosphere. Numerical modelling demonstrates that the number of filaments depends on charge-to-mass ratio of dust.

Monte Carlo variance reduction approaches for non-Boltzmann tallies

International Nuclear Information System (INIS)

Booth, T.E.

1992-12-01

Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed

Discussion on variance reduction technique for shielding

Energy Technology Data Exchange (ETDEWEB)

Maekawa, Fujio [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

1998-03-01

As the task of the engineering design activity of the international thermonuclear fusion experimental reactor (ITER), on 316 type stainless steel (SS316) and the compound system of SS316 and water, the shielding experiment using the D-T neutron source of FNS in Japan Atomic Energy Research Institute has been carried out. However, in these analyses, enormous working time and computing time were required for determining the Weight Window parameter. Limitation or complication was felt when the variance reduction by Weight Window method of MCNP code was carried out. For the purpose of avoiding this difficulty, investigation was performed on the effectiveness of the variance reduction by cell importance method. The conditions of calculation in all cases are shown. As the results, the distribution of fractional standard deviation (FSD) related to neutrons and gamma-ray flux in the direction of shield depth is reported. There is the optimal importance change, and when importance was increased at the same rate as that of the attenuation of neutron or gamma-ray flux, the optimal variance reduction can be done. (K.I.)

Estimating integrated variance in the presence of microstructure noise using linear regression

Science.gov (United States)

Holý, Vladimír

2017-07-01

Using financial high-frequency data for estimation of integrated variance of asset prices is beneficial but with increasing number of observations so-called microstructure noise occurs. This noise can significantly bias the realized variance estimator. We propose a method for estimation of the integrated variance robust to microstructure noise as well as for testing the presence of the noise. Our method utilizes linear regression in which realized variances estimated from different data subsamples act as dependent variable while the number of observations act as explanatory variable. We compare proposed estimator with other methods on simulated data for several microstructure noise structures.

Approximation errors during variance propagation

International Nuclear Information System (INIS)

Dinsmore, Stephen

1986-01-01

Risk and reliability analyses are often performed by constructing and quantifying large fault trees. The inputs to these models are component failure events whose probability of occuring are best represented as random variables. This paper examines the errors inherent in two approximation techniques used to calculate the top event's variance from the inputs' variance. Two sample fault trees are evaluated and several three dimensional plots illustrating the magnitude of the error over a wide range of input means and variances are given

The response of a simulated mesoscale convective system to increased aerosol pollution: Part II: Derecho characteristics and intensity in response to increased pollution

Science.gov (United States)

Clavner, Michal; Grasso, Lewis D.; Cotton, William R.; van den Heever, Susan C.

2018-01-01

Mesoscale Convective Systems (MCS) are important contributors to rainfall as well as producers of severe weather such as hail, tornados, and straight-line wind events known as derechos. In this study, different aerosol concentrations and their effects on a derecho event are examined by simulating a case study, the 8 May 2009 "Super-Derecho", using the Regional Atmospheric Modeling System (RAMS), a cloud-resolving model with sophisticated aerosol and cloud microphysics. Three simulations were conducted that differed in the initial aerosol concentrations, spatial distribution and chemical composition as derived from output of GEOS-Chem, a 3D chemical transport model. In order to understand the impact of changes in aerosol concentrations on the derecho characteristics, the dynamical processes that produced the strong surface wind were determined by performing back-trajectory analysis during two periods of the simulated storm: the development and the onset of dissipation. A time dependent and non-monotonic trend was found between the intensity of the derecho and the increased aerosol concentrations that served as cloud condensation nuclei. During the formation period of the MCS, the non-monotonic trend was attributed to the microphysical impact of aerosol loading on the intensity of the cold pool; that is, the impact of aerosols on both the melting and evaporation rates of hydrometeors. The subsequent intensity changes within the cold pool modified the balance between the horizontal vorticity generated by the cold pool and that of the environment, thereby impacting the orientation of the convective updraft at the leading line. This, in turn, altered the primary flow that contributed to the formation of the derecho-strength surface winds. The simulation with no anthropogenic aerosols exhibited the strongest cold pool and the primary flow was associated with a descending rear inflow jet that produced the derecho winds over a larger region. The simulation with the highest

Thermospheric mass density model error variance as a function of time scale

Science.gov (United States)

Emmert, J. T.; Sutton, E. K.

2017-12-01

In the increasingly crowded low-Earth orbit environment, accurate estimation of orbit prediction uncertainties is essential for collision avoidance. Poor characterization of such uncertainty can result in unnecessary and costly avoidance maneuvers (false positives) or disregard of a collision risk (false negatives). Atmospheric drag is a major source of orbit prediction uncertainty, and is particularly challenging to account for because it exerts a cumulative influence on orbital trajectories and is therefore not amenable to representation by a single uncertainty parameter. To address this challenge, we examine the variance of measured accelerometer-derived and orbit-derived mass densities with respect to predictions by thermospheric empirical models, using the data-minus-model variance as a proxy for model uncertainty. Our analysis focuses mainly on the power spectrum of the residuals, and we construct an empirical model of the variance as a function of time scale (from 1 hour to 10 years), altitude, and solar activity. We find that the power spectral density approximately follows a power-law process but with an enhancement near the 27-day solar rotation period. The residual variance increases monotonically with altitude between 250 and 550 km. There are two components to the variance dependence on solar activity: one component is 180 degrees out of phase (largest variance at solar minimum), and the other component lags 2 years behind solar maximum (largest variance in the descending phase of the solar cycle).

The phenotypic variance gradient - a novel concept.

Science.gov (United States)

Pertoldi, Cino; Bundgaard, Jørgen; Loeschcke, Volker; Barker, James Stuart Flinton

2014-11-01

Evolutionary ecologists commonly use reaction norms, which show the range of phenotypes produced by a set of genotypes exposed to different environments, to quantify the degree of phenotypic variance and the magnitude of plasticity of morphometric and life-history traits. Significant differences among the values of the slopes of the reaction norms are interpreted as significant differences in phenotypic plasticity, whereas significant differences among phenotypic variances (variance or coefficient of variation) are interpreted as differences in the degree of developmental instability or canalization. We highlight some potential problems with this approach to quantifying phenotypic variance and suggest a novel and more informative way to plot reaction norms: namely "a plot of log (variance) on the y-axis versus log (mean) on the x-axis, with a reference line added". This approach gives an immediate impression of how the degree of phenotypic variance varies across an environmental gradient, taking into account the consequences of the scaling effect of the variance with the mean. The evolutionary implications of the variation in the degree of phenotypic variance, which we call a "phenotypic variance gradient", are discussed together with its potential interactions with variation in the degree of phenotypic plasticity and canalization.

Confidence Interval Approximation For Treatment Variance In ...

African Journals Online (AJOL)

In a random effects model with a single factor, variation is partitioned into two as residual error variance and treatment variance. While a confidence interval can be imposed on the residual error variance, it is not possible to construct an exact confidence interval for the treatment variance. This is because the treatment ...

Portfolio optimization with mean-variance model

Science.gov (United States)

Hoe, Lam Weng; Siew, Lam Weng

2016-06-01

Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

A New Result Concerning the Solvability of a Class of General Systems of Variational Equations with Nonmonotone Operators: Applications to Dirichlet and Neumann Nonlinear Problems

Directory of Open Access Journals (Sweden)

Luisa Toscano

2016-01-01

Full Text Available A new result of solvability for a wide class of systems of variational equations depending on parameters and governed by nonmonotone operators is found in a Banach real and reflexive space with applications to Dirichlet and Neumann problems related to nonlinear elliptic systems.

Effect of Pulse Polarity on Thresholds and on Non-monotonic Loudness Growth in Cochlear Implant Users.

Science.gov (United States)

Macherey, Olivier; Carlyon, Robert P; Chatron, Jacques; Roman, Stéphane

2017-06-01

Most cochlear implants (CIs) activate their electrodes non-simultaneously in order to eliminate electrical field interactions. However, the membrane of auditory nerve fibers needs time to return to its resting state, causing the probability of firing to a pulse to be affected by previous pulses. Here, we provide new evidence on the effect of pulse polarity and current level on these interactions. In experiment 1, detection thresholds and most comfortable levels (MCLs) were measured in CI users for 100-Hz pulse trains consisting of two consecutive biphasic pulses of the same or of opposite polarity. All combinations of polarities were studied: anodic-cathodic-anodic-cathodic (ACAC), CACA, ACCA, and CAAC. Thresholds were lower when the adjacent phases of the two pulses had the same polarity (ACCA and CAAC) than when they were different (ACAC and CACA). Some subjects showed a lower threshold for ACCA than for CAAC while others showed the opposite trend demonstrating that polarity sensitivity at threshold is genuine and subject- or electrode-dependent. In contrast, anodic (CAAC) pulses always showed a lower MCL than cathodic (ACCA) pulses, confirming previous reports. In experiments 2 and 3, the subjects compared the loudness of several pulse trains differing in current level separately for ACCA and CAAC. For 40 % of the electrodes tested, loudness grew non-monotonically as a function of current level for ACCA but never for CAAC. This finding may relate to a conduction block of the action potentials along the fibers induced by a strong hyperpolarization of their central processes. Further analysis showed that the electrodes showing a lower threshold for ACCA than for CAAC were more likely to yield a non-monotonic loudness growth. It is proposed that polarity sensitivity at threshold reflects the local neural health and that anodic asymmetric pulses should preferably be used to convey sound information while avoiding abnormal loudness percepts.

Least-squares variance component estimation

NARCIS (Netherlands)

Teunissen, P.J.G.; Amiri-Simkooei, A.R.

2007-01-01

Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible because it works with a user-defined weight

Nonmonotonic magnetoresistance of a two-dimensional viscous electron-hole fluid in a confined geometry

Science.gov (United States)

Alekseev, P. S.; Dmitriev, A. P.; Gornyi, I. V.; Kachorovskii, V. Yu.; Narozhny, B. N.; Titov, M.

2018-02-01

Ultrapure conductors may exhibit hydrodynamic transport where the collective motion of charge carriers resembles the flow of a viscous fluid. In a confined geometry (e.g., in ultra-high-quality nanostructures), the electronic fluid assumes a Poiseuille-type flow. Applying an external magnetic field tends to diminish viscous effects leading to large negative magnetoresistance. In two-component systems near charge neutrality, the hydrodynamic flow of charge carriers is strongly affected by the mutual friction between the two constituents. At low fields, the magnetoresistance is negative, however, at high fields the interplay between electron-hole scattering, recombination, and viscosity results in a dramatic change of the flow profile: the magnetoresistance changes its sign and eventually becomes linear in very high fields. This nonmonotonic magnetoresistance can be used as a fingerprint to detect viscous flow in two-component conducting systems.

Origin of the non-monotonic variance of Tc in the 1111 iron based superconductors with isovalent doping

Science.gov (United States)

Usui, Hidetomo; Suzuki, Katsuhiro; Kuroki, Kazuhiko

2015-01-01

Motivated by recent experimental investigations of the isovalent doping iron-based superconductors LaFe(AsxP1-x)O1-yFy and NdFe(AsxP1-x)O1-yFy, we theoretically study the correlation between the local lattice structure, the Fermi surface, the spin fluctuation-mediated superconductivity, and the composition ratio. In the phosphides, the dXZ and dYZ orbitals barely hybridize around the Γ point to give rise to two intersecting ellipse shape Fermi surfaces. As the arsenic content increases and the Fe-As-Fe bond angle is reduced, the hybridization increases, so that the two bands are mixed to result in concentric inner and outer Fermi surfaces, and the orbital character gradually changes to dxz and dyz, where x–y axes are rotated by 45 degrees from X–Y. This makes the orbital matching between the electron and hole Fermi surfaces better and enhances the spin fluctuation within the dxz/yz orbitals. On the other hand, the hybridization splits the two bands, resulting in a more dispersive inner band. Hence, there is a trade-off between the density of states and the orbital matching, thereby locally maximizing the dxz/yz spin fluctuation and superconductivity in the intermediate regime of As/P ratio. The consistency with the experiment strongly indicate the importance of the spin fluctuation played in this series of superconductors. PMID:26073071

Stair-Step Particle Flux Spectra on the Lunar Surface: Evidence for Nonmonotonic Potentials?

Science.gov (United States)

Collier, Michael R.; Newheart, Anastasia; Poppe, Andrew R.; Hills, H. Kent; Farrell, William M.

2016-01-01

We present examples of unusual "stair-step" differential flux spectra observed by the Apollo 14 Suprathermal Ion Detector Experiment on the lunar dayside surface in Earth's magnetotail. These spectra exhibit a relatively constant differential flux below some cutoff energy and then drop off precipitously, by about an order of magnitude or more, at higher energies. We propose that these spectra result from photoions accelerated on the lunar dayside by nonmonotonic potentials (i.e.,potentials that do not decay to zero monotonically) and present a model for the expected differential flux. The energy of the cutoff and the magnitude of the differential flux are related to the properties of the local space environment and are consistent with the observed flux spectra. If this interpretation is correct, these surface-based ion observations provide a unique perspective that both complements and enhances the conclusions obtained by remote-sensing orbiter observations on the Moon's exospheric and electrostatic properties.

Genetic variants influencing phenotypic variance heterogeneity.

Science.gov (United States)

Ek, Weronica E; Rask-Andersen, Mathias; Karlsson, Torgny; Enroth, Stefan; Gyllensten, Ulf; Johansson, Åsa

2018-03-01

Most genetic studies identify genetic variants associated with disease risk or with the mean value of a quantitative trait. More rarely, genetic variants associated with variance heterogeneity are considered. In this study, we have identified such variance single-nucleotide polymorphisms (vSNPs) and examined if these represent biological gene × gene or gene × environment interactions or statistical artifacts caused by multiple linked genetic variants influencing the same phenotype. We have performed a genome-wide study, to identify vSNPs associated with variance heterogeneity in DNA methylation levels. Genotype data from over 10 million single-nucleotide polymorphisms (SNPs), and DNA methylation levels at over 430 000 CpG sites, were analyzed in 729 individuals. We identified vSNPs for 7195 CpG sites (P mean DNA methylation levels. We further showed that variance heterogeneity between genotypes mainly represents additional, often rare, SNPs in linkage disequilibrium (LD) with the respective vSNP and for some vSNPs, multiple low frequency variants co-segregating with one of the vSNP alleles. Therefore, our results suggest that variance heterogeneity of DNA methylation mainly represents phenotypic effects by multiple SNPs, rather than biological interactions. Such effects may also be important for interpreting variance heterogeneity of more complex clinical phenotypes.

An efficient sampling approach for variance-based sensitivity analysis based on the law of total variance in the successive intervals without overlapping

Science.gov (United States)

Yun, Wanying; Lu, Zhenzhou; Jiang, Xian

2018-06-01

To efficiently execute the variance-based global sensitivity analysis, the law of total variance in the successive intervals without overlapping is proved at first, on which an efficient space-partition sampling-based approach is subsequently proposed in this paper. Through partitioning the sample points of output into different subsets according to different inputs, the proposed approach can efficiently evaluate all the main effects concurrently by one group of sample points. In addition, there is no need for optimizing the partition scheme in the proposed approach. The maximum length of subintervals is decreased by increasing the number of sample points of model input variables in the proposed approach, which guarantees the convergence condition of the space-partition approach well. Furthermore, a new interpretation on the thought of partition is illuminated from the perspective of the variance ratio function. Finally, three test examples and one engineering application are employed to demonstrate the accuracy, efficiency and robustness of the proposed approach.

A comparison of 3-D computed tomography versus 2-D radiography measurements of ulnar variance and ulnolunate distance during forearm rotation.

Science.gov (United States)

Kawanishi, Y; Moritomo, H; Omori, S; Kataoka, T; Murase, T; Sugamoto, K

2014-06-01

Positive ulnar variance is associated with ulnar impaction syndrome and ulnar variance is reported to increase with pronation. However, radiographic measurement can be affected markedly by the incident angle of the X-ray beam. We performed three-dimensional (3-D) computed tomography measurements of ulnar variance and ulnolunate distance during forearm rotation and compared these with plain radiographic measurements in 15 healthy wrists. From supination to pronation, ulnar variance increased in all cases on the radiographs; mean ulnar variance increased significantly and mean ulnolunate distance decreased significantly. However on 3-D imaging, ulna variance decreased in 12 cases on moving into pronation and increased in three cases; neither the mean ulnar variance nor mean ulnolunate distance changed significantly. Our results suggest that the forearm position in which ulnar variance increased varies among individuals. This may explain why some patients with ulnar impaction syndrome complain of wrist pain exacerbated by forearm supination. It also suggests that standard radiographic assessments of ulnar variance are unreliable. © The Author(s) 2013.

Reduction of treatment delivery variances with a computer-controlled treatment delivery system

International Nuclear Information System (INIS)

Fraass, B.A.; Lash, K.L.; Matrone, G.M.; Lichter, A.S.

1997-01-01

does not depend on fixed therapist staff on particular machines. Results: The overall reported variance rate (all treatments, machines) was < 0.1 % per port or 0.33 % per treatment session. The rate (per machine) depended on automation and plan complexity (see table). Machine M4 (most complex plans and most automation) had the lowest variance rate. The variance rate decreased with increasing automation in spite of increasing plan complexity, while for the manual machines the variance rate increased with complexity. Note that the real variance rates on the two manual machines must be higher than shown here, while (particularly on M4) virtually all random treatment delivery errors were noted by the CCRS system and its QA checks. Treatment delivery times averaged from 14 to 23 minutes per plan, and depended on ports/plan, although this analysis is complicated by other factors. Conclusion: Use of a sophisticated computer-controlled delivery system for routine patient treatments with complex 3-D conformal plans has led to a significant decrease in treatment delivery variances, while at the same time allowing delivery of increasingly complex and sophisticated conformal plans without a significant increase in treatment time. With renewed vigilance for the possibility of systematic problems, it is clear that use of complete and integrated computer-controlled delivery systems can provide significant improvements in treatment delivery, since better plans can be delivered with significantly fewer errors, and without significantly increasing treatment time

How does variance in fertility change over the demographic transition?

Science.gov (United States)

Hruschka, Daniel J; Burger, Oskar

2016-04-19

Most work on the human fertility transition has focused on declines in mean fertility. However, understanding changes in the variance of reproductive outcomes can be equally important for evolutionary questions about the heritability of fertility, individual determinants of fertility and changing patterns of reproductive skew. Here, we document how variance in completed fertility among women (45-49 years) differs across 200 surveys in 72 low- to middle-income countries where fertility transitions are currently in progress at various stages. Nearly all (91%) of samples exhibit variance consistent with a Poisson process of fertility, which places systematic, and often severe, theoretical upper bounds on the proportion of variance that can be attributed to individual differences. In contrast to the pattern of total variance, these upper bounds increase from high- to mid-fertility samples, then decline again as samples move from mid to low fertility. Notably, the lowest fertility samples often deviate from a Poisson process. This suggests that as populations move to low fertility their reproduction shifts from a rate-based process to a focus on an ideal number of children. We discuss the implications of these findings for predicting completed fertility from individual-level variables. © 2016 The Author(s).

Speed Variance and Its Influence on Accidents.

Science.gov (United States)

Garber, Nicholas J.; Gadirau, Ravi

A study was conducted to investigate the traffic engineering factors that influence speed variance and to determine to what extent speed variance affects accident rates. Detailed analyses were carried out to relate speed variance with posted speed limit, design speeds, and other traffic variables. The major factor identified was the difference…

A stable route to high-{beta}{sub p} plasmas with non-monotonic q-profiles

Energy Technology Data Exchange (ETDEWEB)

Soeldner, F X; Baranov, Y; Bhatnagar, V P; Bickley, A J; Challis, C D; Fischer, B; Gormezano, C; Huysmans, G T.A.; Kerner, W; Rimini, F; Sips, A C.C.; Springmann, R; Taroni, A [Commission of the European Communities, Abingdon (United Kingdom). JET Joint Undertaking; Goedbloed, J P; Holties, H A [Institute for Plasmas Physics, Nieuwegein (Netherlands); Parail, V V; Pereverzev, G V [Kurchatov Institute of Atomic Energy, Moscow (Russian Federation)

1994-07-01

Steady-state operation of tokamak reactors seems feasible in so-called Advanced Scenarios with high bootstrap current in high-beta{sub p} operation. The stabilization of such discharges with noninductive profile control will be attempted on JET in pursuit of previous high bootstrap current studies. Results of modelling studies of full noninductive current drive scenarios in JET and ITER are presented. Fast Waves (FW), Lower Hybrid (LH) Waves and Neutral Beam Injection (NBI) are used for heating and current drive, alternatively or in combination. A stable route to nonmonotonic q-profiles has been found with a specific ramp-up scenario which combines LH-current drive (LHCD) and a fast Ohmic ramp-up. A hollow current profile with deep shear reversal over the whole central region is thereby formed in an early low-beta phase and frozen in by additional heating. (authors). 5 refs., 4 figs.

Investigation on de-trapping mechanisms related to non-monotonic kink pattern in GaN HEMT devices

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Chandan Sharma

2017-08-01

Full Text Available This article reports an experimental approach to analyze the kink effect phenomenon which is usually observed during the GaN high electron mobility transistor (HEMT operation. De-trapping of charge carriers is one of the prominent reasons behind the kink effect. The commonly observed non-monotonic behavior of kink pattern is analyzed under two different device operating conditions and it is found that two different de-trapping mechanisms are responsible for a particular kink behavior. These different de-trapping mechanisms are investigated through a time delay analysis which shows the presence of traps with different time constants. Further voltage sweep and temperature analysis corroborates the finding that different de-trapping mechanisms play a role in kink behavior under different device operating conditions.

Investigation on de-trapping mechanisms related to non-monotonic kink pattern in GaN HEMT devices

Science.gov (United States)

Sharma, Chandan; Laishram, Robert; Amit, Rawal, Dipendra Singh; Vinayak, Seema; Singh, Rajendra

2017-08-01

This article reports an experimental approach to analyze the kink effect phenomenon which is usually observed during the GaN high electron mobility transistor (HEMT) operation. De-trapping of charge carriers is one of the prominent reasons behind the kink effect. The commonly observed non-monotonic behavior of kink pattern is analyzed under two different device operating conditions and it is found that two different de-trapping mechanisms are responsible for a particular kink behavior. These different de-trapping mechanisms are investigated through a time delay analysis which shows the presence of traps with different time constants. Further voltage sweep and temperature analysis corroborates the finding that different de-trapping mechanisms play a role in kink behavior under different device operating conditions.

Volatility and variance swaps : A comparison of quantitative models to calculate the fair volatility and variance strike

OpenAIRE

Röring, Johan

2017-01-01

Volatility is a common risk measure in the field of finance that describes the magnitude of an asset’s up and down movement. From only being a risk measure, volatility has become an asset class of its own and volatility derivatives enable traders to get an isolated exposure to an asset’s volatility. Two kinds of volatility derivatives are volatility swaps and variance swaps. The problem with volatility swaps and variance swaps is that they require estimations of the future variance and volati...

Local variances in biomonitoring

International Nuclear Information System (INIS)

Wolterbeek, H.T.

1999-01-01

The present study deals with the (larger-scaled) biomonitoring survey and specifically focuses on the sampling site. In most surveys, the sampling site is simply selected or defined as a spot of (geographical) dimensions which is small relative to the dimensions of the total survey area. Implicitly it is assumed that the sampling site is essentially homogeneous with respect to the investigated variation in survey parameters. As such, the sampling site is mostly regarded as 'the basic unit' of the survey. As a logical consequence, the local (sampling site) variance should also be seen as a basic and important characteristic of the survey. During the study, work is carried out to gain more knowledge of the local variance. Multiple sampling is carried out at a specific site (tree bark, mosses, soils), multi-elemental analyses are carried out by NAA, and local variances are investigated by conventional statistics, factor analytical techniques, and bootstrapping. Consequences of the outcomes are discussed in the context of sampling, sample handling and survey quality. (author)

Variance components for body weight in Japanese quails (Coturnix japonica

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RO Resende

2005-03-01

Full Text Available The objective of this study was to estimate the variance components for body weight in Japanese quails by Bayesian procedures. The body weight at hatch (BWH and at 7 (BW07, 14 (BW14, 21 (BW21 and 28 days of age (BW28 of 3,520 quails was recorded from August 2001 to June 2002. A multiple-trait animal model with additive genetic, maternal environment and residual effects was implemented by Gibbs sampling methodology. A single Gibbs sampling with 80,000 rounds was generated by the program MTGSAM (Multiple Trait Gibbs Sampling in Animal Model. Normal and inverted Wishart distributions were used as prior distributions for the random effects and the variance components, respectively. Variance components were estimated based on the 500 samples that were left after elimination of 30,000 rounds in the burn-in period and 100 rounds of each thinning interval. The posterior means of additive genetic variance components were 0.15; 4.18; 14.62; 27.18 and 32.68; the posterior means of maternal environment variance components were 0.23; 1.29; 2.76; 4.12 and 5.16; and the posterior means of residual variance components were 0.084; 6.43; 22.66; 31.21 and 30.85, at hatch, 7, 14, 21 and 28 days old, respectively. The posterior means of heritability were 0.33; 0.35; 0.36; 0.43 and 0.47 at hatch, 7, 14, 21 and 28 days old, respectively. These results indicate that heritability increased with age. On the other hand, after hatch there was a marked reduction in the maternal environment variance proportion of the phenotypic variance, whose estimates were 0.50; 0.11; 0.07; 0.07 and 0.08 for BWH, BW07, BW14, BW21 and BW28, respectively. The genetic correlation between weights at different ages was high, except for those estimates between BWH and weight at other ages. Changes in body weight of quails can be efficiently achieved by selection.

Variance-to-mean method generalized by linear difference filter technique

International Nuclear Information System (INIS)

Hashimoto, Kengo; Ohsaki, Hiroshi; Horiguchi, Tetsuo; Yamane, Yoshihiro; Shiroya, Seiji

1998-01-01

The conventional variance-to-mean method (Feynman-α method) seriously suffers the divergency of the variance under such a transient condition as a reactor power drift. Strictly speaking, then, the use of the Feynman-α is restricted to a steady state. To apply the method to more practical uses, it is desirable to overcome this kind of difficulty. For this purpose, we propose an usage of higher-order difference filter technique to reduce the effect of the reactor power drift, and derive several new formulae taking account of the filtering. The capability of the formulae proposed was demonstrated through experiments in the Kyoto University Critical Assembly. The experimental results indicate that the divergency of the variance can be effectively suppressed by the filtering technique, and that the higher-order filter becomes necessary with increasing variation rate in power

Non-monotonic reorganization of brain networks with Alzheimer’s disease progression

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Hyoungkyu eKim

2015-06-01

Full Text Available Background: Identification of stage-specific changes in brain network of patients with Alzheimer’s disease (AD is critical for rationally designed therapeutics that delays the progression of the disease. However, pathological neural processes and their resulting changes in brain network topology with disease progression are not clearly known. Methods: The current study was designed to investigate the alterations in network topology of resting state fMRI among patients in three different clinical dementia rating (CDR groups (i.e., CDR = 0.5, 1, 2 and amnestic mild cognitive impairment (aMCI and age-matched healthy subject groups. We constructed cost networks from these 5 groups and analyzed their network properties using graph theoretical measures.Results: The topological properties of AD brain networks differed in a non-monotonic, stage-specific manner. Interestingly, local and global efficiency and betweenness of the network were rather higher in the aMCI and AD (CDR 1 groups than those of prior stage groups. The number, location, and structure of rich-clubs changed dynamically as the disease progressed.Conclusions: The alterations in network topology of the brain are quite dynamic with AD progression, and these dynamic changes in network patterns should be considered meticulously for efficient therapeutic interventions of AD.

Individual and collective bodies: using measures of variance and association in contextual epidemiology.

Science.gov (United States)

Merlo, J; Ohlsson, H; Lynch, K F; Chaix, B; Subramanian, S V

2009-12-01

Social epidemiology investigates both individuals and their collectives. Although the limits that define the individual bodies are very apparent, the collective body's geographical or cultural limits (eg "neighbourhood") are more difficult to discern. Also, epidemiologists normally investigate causation as changes in group means. However, many variables of interest in epidemiology may cause a change in the variance of the distribution of the dependent variable. In spite of that, variance is normally considered a measure of uncertainty or a nuisance rather than a source of substantive information. This reasoning is also true in many multilevel investigations, whereas understanding the distribution of variance across levels should be fundamental. This means-centric reductionism is mostly concerned with risk factors and creates a paradoxical situation, as social medicine is not only interested in increasing the (mean) health of the population, but also in understanding and decreasing inappropriate health and health care inequalities (variance). Critical essay and literature review. The present study promotes (a) the application of measures of variance and clustering to evaluate the boundaries one uses in defining collective levels of analysis (eg neighbourhoods), (b) the combined use of measures of variance and means-centric measures of association, and (c) the investigation of causes of health variation (variance-altering causation). Both measures of variance and means-centric measures of association need to be included when performing contextual analyses. The variance approach, a new aspect of contextual analysis that cannot be interpreted in means-centric terms, allows perspectives to be expanded.

Dynamic Mean-Variance Asset Allocation

OpenAIRE

Basak, Suleyman; Chabakauri, Georgy

2009-01-01

Mean-variance criteria remain prevalent in multi-period problems, and yet not much is known about their dynamically optimal policies. We provide a fully analytical characterization of the optimal dynamic mean-variance portfolios within a general incomplete-market economy, and recover a simple structure that also inherits several conventional properties of static models. We also identify a probability measure that incorporates intertemporal hedging demands and facilitates much tractability in ...

The Variance Composition of Firm Growth Rates

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Luiz Artur Ledur Brito

2009-04-01

Full Text Available Firms exhibit a wide variability in growth rates. This can be seen as another manifestation of the fact that firms are different from one another in several respects. This study investigated this variability using the variance components technique previously used to decompose the variance of financial performance. The main source of variation in growth rates, responsible for more than 40% of total variance, corresponds to individual, idiosyncratic firm aspects and not to industry, country, or macroeconomic conditions prevailing in specific years. Firm growth, similar to financial performance, is mostly unique to specific firms and not an industry or country related phenomenon. This finding also justifies using growth as an alternative outcome of superior firm resources and as a complementary dimension of competitive advantage. This also links this research with the resource-based view of strategy. Country was the second source of variation with around 10% of total variance. The analysis was done using the Compustat Global database with 80,320 observations, comprising 13,221 companies in 47 countries, covering the years of 1994 to 2002. It also compared the variance structure of growth to the variance structure of financial performance in the same sample.

Estimating the encounter rate variance in distance sampling

Science.gov (United States)

Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.

2009-01-01

The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.

Science.gov (United States)

Thompson, William Hedley; Fransson, Peter

2016-12-01

Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

Towards the ultimate variance-conserving convection scheme

International Nuclear Information System (INIS)

Os, J.J.A.M. van; Uittenbogaard, R.E.

2004-01-01

In the past various arguments have been used for applying kinetic energy-conserving advection schemes in numerical simulations of incompressible fluid flows. One argument is obeying the programmed dissipation by viscous stresses or by sub-grid stresses in Direct Numerical Simulation and Large Eddy Simulation, see e.g. [Phys. Fluids A 3 (7) (1991) 1766]. Another argument is that, according to e.g. [J. Comput. Phys. 6 (1970) 392; 1 (1966) 119], energy-conserving convection schemes are more stable i.e. by prohibiting a spurious blow-up of volume-integrated energy in a closed volume without external energy sources. In the above-mentioned references it is stated that nonlinear instability is due to spatial truncation rather than to time truncation and therefore these papers are mainly concerned with the spatial integration. In this paper we demonstrate that discretized temporal integration of a spatially variance-conserving convection scheme can induce non-energy conserving solutions. In this paper the conservation of the variance of a scalar property is taken as a simple model for the conservation of kinetic energy. In addition, the derivation and testing of a variance-conserving scheme allows for a clear definition of kinetic energy-conserving advection schemes for solving the Navier-Stokes equations. Consequently, we first derive and test a strictly variance-conserving space-time discretization for the convection term in the convection-diffusion equation. Our starting point is the variance-conserving spatial discretization of the convection operator presented by Piacsek and Williams [J. Comput. Phys. 6 (1970) 392]. In terms of its conservation properties, our variance-conserving scheme is compared to other spatially variance-conserving schemes as well as with the non-variance-conserving schemes applied in our shallow-water solver, see e.g. [Direct and Large-eddy Simulation Workshop IV, ERCOFTAC Series, Kluwer Academic Publishers, 2001, pp. 409-287

The Distribution of the Sample Minimum-Variance Frontier

OpenAIRE

Raymond Kan; Daniel R. Smith

2008-01-01

In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us t...

Minimum variance and variance of outgoing quality limit MDS-1(c1, c2) plans

Science.gov (United States)

Raju, C.; Vidya, R.

2016-06-01

In this article, the outgoing quality (OQ) and total inspection (TI) of multiple deferred state sampling plans MDS-1(c1,c2) are studied. It is assumed that the inspection is rejection rectification. Procedures for designing MDS-1(c1,c2) sampling plans with minimum variance of OQ and TI are developed. A procedure for obtaining a plan for a designated upper limit for the variance of the OQ (VOQL) is outlined.

Genotypic-specific variance in Caenorhabditis elegans lifetime fecundity.

Science.gov (United States)

Diaz, S Anaid; Viney, Mark

2014-06-01

Organisms live in heterogeneous environments, so strategies that maximze fitness in such environments will evolve. Variation in traits is important because it is the raw material on which natural selection acts during evolution. Phenotypic variation is usually thought to be due to genetic variation and/or environmentally induced effects. Therefore, genetically identical individuals in a constant environment should have invariant traits. Clearly, genetically identical individuals do differ phenotypically, usually thought to be due to stochastic processes. It is now becoming clear, especially from studies of unicellular species, that phenotypic variance among genetically identical individuals in a constant environment can be genetically controlled and that therefore, in principle, this can be subject to selection. However, there has been little investigation of these phenomena in multicellular species. Here, we have studied the mean lifetime fecundity (thus a trait likely to be relevant to reproductive success), and variance in lifetime fecundity, in recently-wild isolates of the model nematode Caenorhabditis elegans. We found that these genotypes differed in their variance in lifetime fecundity: some had high variance in fecundity, others very low variance. We find that this variance in lifetime fecundity was negatively related to the mean lifetime fecundity of the lines, and that the variance of the lines was positively correlated between environments. We suggest that the variance in lifetime fecundity may be a bet-hedging strategy used by this species.

Speeding up microevolution: the effects of increasing temperature on selection and genetic variance in a wild bird population

NARCIS (Netherlands)

Husby, A.; Visser, M.E.; Kruuk, L.E.B.

2011-01-01

The amount of genetic variance underlying a phenotypic trait and the strength of selection acting on that trait are two key parameters that determine any evolutionary response to selection. Despite substantial evidence that, in natural populations, both parameters may vary across environmental

Discrete and continuous time dynamic mean-variance analysis

OpenAIRE

Reiss, Ariane

1999-01-01

Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...

Estimation of noise-free variance to measure heterogeneity.

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Tilo Winkler

Full Text Available Variance is a statistical parameter used to characterize heterogeneity or variability in data sets. However, measurements commonly include noise, as random errors superimposed to the actual value, which may substantially increase the variance compared to a noise-free data set. Our aim was to develop and validate a method to estimate noise-free spatial heterogeneity of pulmonary perfusion using dynamic positron emission tomography (PET scans. On theoretical grounds, we demonstrate a linear relationship between the total variance of a data set derived from averages of n multiple measurements, and the reciprocal of n. Using multiple measurements with varying n yields estimates of the linear relationship including the noise-free variance as the constant parameter. In PET images, n is proportional to the number of registered decay events, and the variance of the image is typically normalized by the square of its mean value yielding a coefficient of variation squared (CV(2. The method was evaluated with a Jaszczak phantom as reference spatial heterogeneity (CV(r(2 for comparison with our estimate of noise-free or 'true' heterogeneity (CV(t(2. We found that CV(t(2 was only 5.4% higher than CV(r2. Additional evaluations were conducted on 38 PET scans of pulmonary perfusion using (13NN-saline injection. The mean CV(t(2 was 0.10 (range: 0.03-0.30, while the mean CV(2 including noise was 0.24 (range: 0.10-0.59. CV(t(2 was in average 41.5% of the CV(2 measured including noise (range: 17.8-71.2%. The reproducibility of CV(t(2 was evaluated using three repeated PET scans from five subjects. Individual CV(t(2 were within 16% of each subject's mean and paired t-tests revealed no difference among the results from the three consecutive PET scans. In conclusion, our method provides reliable noise-free estimates of CV(t(2 in PET scans, and may be useful for similar statistical problems in experimental data.

Nonlinear Epigenetic Variance: Review and Simulations

Science.gov (United States)

Kan, Kees-Jan; Ploeger, Annemie; Raijmakers, Maartje E. J.; Dolan, Conor V.; van Der Maas, Han L. J.

2010-01-01

We present a review of empirical evidence that suggests that a substantial portion of phenotypic variance is due to nonlinear (epigenetic) processes during ontogenesis. The role of such processes as a source of phenotypic variance in human behaviour genetic studies is not fully appreciated. In addition to our review, we present simulation studies…

Complex, non-monotonic dose-response curves with multiple maxima: Do we (ever) sample densely enough?

Science.gov (United States)

Cvrčková, Fatima; Luštinec, Jiří; Žárský, Viktor

2015-01-01

We usually expect the dose-response curves of biological responses to quantifiable stimuli to be simple, either monotonic or exhibiting a single maximum or minimum. Deviations are often viewed as experimental noise. However, detailed measurements in plant primary tissue cultures (stem pith explants of kale and tobacco) exposed to varying doses of sucrose, cytokinins (BA or kinetin) or auxins (IAA or NAA) revealed that growth and several biochemical parameters exhibit multiple reproducible, statistically significant maxima over a wide range of exogenous substance concentrations. This results in complex, non-monotonic dose-response curves, reminiscent of previous reports of analogous observations in both metazoan and plant systems responding to diverse pharmacological treatments. These findings suggest the existence of a hitherto neglected class of biological phenomena resulting in dose-response curves exhibiting periodic patterns of maxima and minima, whose causes remain so far uncharacterized, partly due to insufficient sampling frequency used in many studies.

Revision: Variance Inflation in Regression

Directory of Open Access Journals (Sweden)

D. R. Jensen

2013-01-01

the intercept; and (iv variance deflation may occur, where ill-conditioned data yield smaller variances than their orthogonal surrogates. Conventional VIFs have all regressors linked, or none, often untenable in practice. Beyond these, our models enable the unlinking of regressors that can be unlinked, while preserving dependence among those intrinsically linked. Moreover, known collinearity indices are extended to encompass angles between subspaces of regressors. To reaccess ill-conditioned data, we consider case studies ranging from elementary examples to data from the literature.

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling

Directory of Open Access Journals (Sweden)

Anna A. Igolkina

2018-06-01

Full Text Available Schizophrenia (SCZ is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells. Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70 by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology

Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar).

Science.gov (United States)

Sonesson, Anna K; Odegård, Jørgen; Rönnegård, Lars

2013-10-17

Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects. Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects. Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro

Variance estimation for generalized Cavalieri estimators

OpenAIRE

Johanna Ziegel; Eva B. Vedel Jensen; Karl-Anton Dorph-Petersen

2011-01-01

The precision of stereological estimators based on systematic sampling is of great practical importance. This paper presents methods of data-based variance estimation for generalized Cavalieri estimators where errors in sampling positions may occur. Variance estimators are derived under perturbed systematic sampling, systematic sampling with cumulative errors and systematic sampling with random dropouts. Copyright 2011, Oxford University Press.

APPLICATION OF A PRIMAL-DUAL INTERIOR POINT ALGORITHM USING EXACT SECOND ORDER INFORMATION WITH A NOVEL NON-MONOTONE LINE SEARCH METHOD TO GENERALLY CONSTRAINED MINIMAX OPTIMISATION PROBLEMS

Directory of Open Access Journals (Sweden)

INTAN S. AHMAD

2008-04-01

Full Text Available This work presents the application of a primal-dual interior point method to minimax optimisation problems. The algorithm differs significantly from previous approaches as it involves a novel non-monotone line search procedure, which is based on the use of standard penalty methods as the merit function used for line search. The crucial novel concept is the discretisation of the penalty parameter used over a finite range of orders of magnitude and the provision of a memory list for each such order. An implementation within a logarithmic barrier algorithm for bounds handling is presented with capabilities for large scale application. Case studies presented demonstrate the capabilities of the proposed methodology, which relies on the reformulation of minimax models into standard nonlinear optimisation models. Some previously reported case studies from the open literature have been solved, and with significantly better optimal solutions identified. We believe that the nature of the non-monotone line search scheme allows the search procedure to escape from local minima, hence the encouraging results obtained.

Influence of Family Structure on Variance Decomposition

DEFF Research Database (Denmark)

Edwards, Stefan McKinnon; Sarup, Pernille Merete; Sørensen, Peter

Partitioning genetic variance by sets of randomly sampled genes for complex traits in D. melanogaster and B. taurus, has revealed that population structure can affect variance decomposition. In fruit flies, we found that a high likelihood ratio is correlated with a high proportion of explained ge...... capturing pure noise. Therefore it is necessary to use both criteria, high likelihood ratio in favor of a more complex genetic model and proportion of genetic variance explained, to identify biologically important gene groups...

Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

International Nuclear Information System (INIS)

Ankirchner, Stefan; Dermoune, Azzouz

2011-01-01

The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.

Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

Energy Technology Data Exchange (ETDEWEB)

Ankirchner, Stefan, E-mail: ankirchner@hcm.uni-bonn.de [Rheinische Friedrich-Wilhelms-Universitaet Bonn, Institut fuer Angewandte Mathematik, Hausdorff Center for Mathematics (Germany); Dermoune, Azzouz, E-mail: Azzouz.Dermoune@math.univ-lille1.fr [Universite des Sciences et Technologies de Lille, Laboratoire Paul Painleve UMR CNRS 8524 (France)

2011-08-15

The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.

Hydrograph variances over different timescales in hydropower production networks

Science.gov (United States)

Zmijewski, Nicholas; Wörman, Anders

2016-08-01

The operation of water reservoirs involves a spectrum of timescales based on the distribution of stream flow travel times between reservoirs, as well as the technical, environmental, and social constraints imposed on the operation. In this research, a hydrodynamically based description of the flow between hydropower stations was implemented to study the relative importance of wave diffusion on the spectrum of hydrograph variance in a regulated watershed. Using spectral decomposition of the effluence hydrograph of a watershed, an exact expression of the variance in the outflow response was derived, as a function of the trends of hydraulic and geomorphologic dispersion and management of production and reservoirs. We show that the power spectra of involved time-series follow nearly fractal patterns, which facilitates examination of the relative importance of wave diffusion and possible changes in production demand on the outflow spectrum. The exact spectral solution can also identify statistical bounds of future demand patterns due to limitations in storage capacity. The impact of the hydraulic description of the stream flow on the reservoir discharge was examined for a given power demand in River Dalälven, Sweden, as function of a stream flow Peclet number. The regulation of hydropower production on the River Dalälven generally increased the short-term variance in the effluence hydrograph, whereas wave diffusion decreased the short-term variance over periods of white noise) as a result of current production objectives.

Chronic exposure to trichloroethylene increases DNA methylation of the Ifng promoter in CD4+ T cells.

Science.gov (United States)

Gilbert, Kathleen M; Blossom, Sarah J; Erickson, Stephen W; Broadfoot, Brannon; West, Kirk; Bai, Shasha; Li, Jingyun; Cooney, Craig A

2016-10-17

CD4 + T cells in female MRL+/+ mice exposed to solvent and water pollutant trichloroethylene (TCE) skew toward effector/memory CD4 + T cells, and demonstrate seemingly non-monotonic alterations in IFN-γ production. In the current study we examined the mechanism for this immunotoxicity using effector/memory and naïve CD4 + T cells isolated every 6 weeks during a 40 week exposure to TCE (0.5mg/ml in drinking water). A time-dependent effect of TCE exposure on both Ifng gene expression and IFN-γ protein production was observed in effector/memory CD4 + T cells, with an increase after 22 weeks of exposure and a decrease after 40 weeks of exposure. No such effect of TCE was observed in naïve CD4 + T cells. A cumulative increase in DNA methylation in the CpG sites of the promoter of the Ifng gene was observed in effector/memory, but not naïve, CD4 + T cells over time. Also unique to the Ifng promoter was an increase in methylation variance in effector/memory compared to naïve CD4 + T cells. Taken together, the CpG sites of the Ifng promoter in effector/memory CD4 + T cells were especially sensitive to the effects of TCE exposure, which may help explain the regulatory effect of the chemical on this gene. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Minimum Variance Portfolios in the Brazilian Equity Market

Directory of Open Access Journals (Sweden)

Alexandre Rubesam

2013-03-01

Full Text Available We investigate minimum variance portfolios in the Brazilian equity market using different methods to estimate the covariance matrix, from the simple model of using the sample covariance to multivariate GARCH models. We compare the performance of the minimum variance portfolios to those of the following benchmarks: (i the IBOVESPA equity index, (ii an equally-weighted portfolio, (iii the maximum Sharpe ratio portfolio and (iv the maximum growth portfolio. Our results show that the minimum variance portfolio has higher returns with lower risk compared to the benchmarks. We also consider long-short 130/30 minimum variance portfolios and obtain similar results. The minimum variance portfolio invests in relatively few stocks with low βs measured with respect to the IBOVESPA index, being easily replicable by individual and institutional investors alike.

Semiparametric approach for non-monotone missing covariates in a parametric regression model

KAUST Repository

Sinha, Samiran

2014-02-26

Missing covariate data often arise in biomedical studies, and analysis of such data that ignores subjects with incomplete information may lead to inefficient and possibly biased estimates. A great deal of attention has been paid to handling a single missing covariate or a monotone pattern of missing data when the missingness mechanism is missing at random. In this article, we propose a semiparametric method for handling non-monotone patterns of missing data. The proposed method relies on the assumption that the missingness mechanism of a variable does not depend on the missing variable itself but may depend on the other missing variables. This mechanism is somewhat less general than the completely non-ignorable mechanism but is sometimes more flexible than the missing at random mechanism where the missingness mechansim is allowed to depend only on the completely observed variables. The proposed approach is robust to misspecification of the distribution of the missing covariates, and the proposed mechanism helps to nullify (or reduce) the problems due to non-identifiability that result from the non-ignorable missingness mechanism. The asymptotic properties of the proposed estimator are derived. Finite sample performance is assessed through simulation studies. Finally, for the purpose of illustration we analyze an endometrial cancer dataset and a hip fracture dataset.

Decomposing variation in male reproductive success: age-specific variances and covariances through extra-pair and within-pair reproduction.

Science.gov (United States)

Lebigre, Christophe; Arcese, Peter; Reid, Jane M

2013-07-01

Age-specific variances and covariances in reproductive success shape the total variance in lifetime reproductive success (LRS), age-specific opportunities for selection, and population demographic variance and effective size. Age-specific (co)variances in reproductive success achieved through different reproductive routes must therefore be quantified to predict population, phenotypic and evolutionary dynamics in age-structured populations. While numerous studies have quantified age-specific variation in mean reproductive success, age-specific variances and covariances in reproductive success, and the contributions of different reproductive routes to these (co)variances, have not been comprehensively quantified in natural populations. We applied 'additive' and 'independent' methods of variance decomposition to complete data describing apparent (social) and realised (genetic) age-specific reproductive success across 11 cohorts of socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia). We thereby quantified age-specific (co)variances in male within-pair and extra-pair reproductive success (WPRS and EPRS) and the contributions of these (co)variances to the total variances in age-specific reproductive success and LRS. 'Additive' decomposition showed that within-age and among-age (co)variances in WPRS across males aged 2-4 years contributed most to the total variance in LRS. Age-specific (co)variances in EPRS contributed relatively little. However, extra-pair reproduction altered age-specific variances in reproductive success relative to the social mating system, and hence altered the relative contributions of age-specific reproductive success to the total variance in LRS. 'Independent' decomposition showed that the (co)variances in age-specific WPRS, EPRS and total reproductive success, and the resulting opportunities for selection, varied substantially across males that survived to each age. Furthermore, extra-pair reproduction increased

Temporal variance reverses the impact of high mean intensity of stress in climate change experiments.

Science.gov (United States)

Benedetti-Cecchi, Lisandro; Bertocci, Iacopo; Vaselli, Stefano; Maggi, Elena

2006-10-01

Extreme climate events produce simultaneous changes to the mean and to the variance of climatic variables over ecological time scales. While several studies have investigated how ecological systems respond to changes in mean values of climate variables, the combined effects of mean and variance are poorly understood. We examined the response of low-shore assemblages of algae and invertebrates of rocky seashores in the northwest Mediterranean to factorial manipulations of mean intensity and temporal variance of aerial exposure, a type of disturbance whose intensity and temporal patterning of occurrence are predicted to change with changing climate conditions. Effects of variance were often in the opposite direction of those elicited by changes in the mean. Increasing aerial exposure at regular intervals had negative effects both on diversity of assemblages and on percent cover of filamentous and coarsely branched algae, but greater temporal variance drastically reduced these effects. The opposite was observed for the abundance of barnacles and encrusting coralline algae, where high temporal variance of aerial exposure either reversed a positive effect of mean intensity (barnacles) or caused a negative effect that did not occur under low temporal variance (encrusting algae). These results provide the first experimental evidence that changes in mean intensity and temporal variance of climatic variables affect natural assemblages of species interactively, suggesting that high temporal variance may mitigate the ecological impacts of ongoing and predicted climate changes.

Integrating Variances into an Analytical Database

Science.gov (United States)

Sanchez, Carlos

2010-01-01

For this project, I enrolled in numerous SATERN courses that taught the basics of database programming. These include: Basic Access 2007 Forms, Introduction to Database Systems, Overview of Database Design, and others. My main job was to create an analytical database that can handle many stored forms and make it easy to interpret and organize. Additionally, I helped improve an existing database and populate it with information. These databases were designed to be used with data from Safety Variances and DCR forms. The research consisted of analyzing the database and comparing the data to find out which entries were repeated the most. If an entry happened to be repeated several times in the database, that would mean that the rule or requirement targeted by that variance has been bypassed many times already and so the requirement may not really be needed, but rather should be changed to allow the variance's conditions permanently. This project did not only restrict itself to the design and development of the database system, but also worked on exporting the data from the database to a different format (e.g. Excel or Word) so it could be analyzed in a simpler fashion. Thanks to the change in format, the data was organized in a spreadsheet that made it possible to sort the data by categories or types and helped speed up searches. Once my work with the database was done, the records of variances could be arranged so that they were displayed in numerical order, or one could search for a specific document targeted by the variances and restrict the search to only include variances that modified a specific requirement. A great part that contributed to my learning was SATERN, NASA's resource for education. Thanks to the SATERN online courses I took over the summer, I was able to learn many new things about computers and databases and also go more in depth into topics I already knew about.

Regional sensitivity analysis using revised mean and variance ratio functions

International Nuclear Information System (INIS)

Wei, Pengfei; Lu, Zhenzhou; Ruan, Wenbin; Song, Jingwen

2014-01-01

The variance ratio function, derived from the contribution to sample variance (CSV) plot, is a regional sensitivity index for studying how much the output deviates from the original mean of model output when the distribution range of one input is reduced and to measure the contribution of different distribution ranges of each input to the variance of model output. In this paper, the revised mean and variance ratio functions are developed for quantifying the actual change of the model output mean and variance, respectively, when one reduces the range of one input. The connection between the revised variance ratio function and the original one is derived and discussed. It is shown that compared with the classical variance ratio function, the revised one is more suitable to the evaluation of model output variance due to reduced ranges of model inputs. A Monte Carlo procedure, which needs only a set of samples for implementing it, is developed for efficiently computing the revised mean and variance ratio functions. The revised mean and variance ratio functions are compared with the classical ones by using the Ishigami function. At last, they are applied to a planar 10-bar structure

Technical Note: On the efficiency of variance reduction techniques for Monte Carlo estimates of imaging noise.

Science.gov (United States)

Sharma, Diksha; Sempau, Josep; Badano, Aldo

2018-02-01

Monte Carlo simulations require large number of histories to obtain reliable estimates of the quantity of interest and its associated statistical uncertainty. Numerous variance reduction techniques (VRTs) have been employed to increase computational efficiency by reducing the statistical uncertainty. We investigate the effect of two VRTs for optical transport methods on accuracy and computing time for the estimation of variance (noise) in x-ray imaging detectors. We describe two VRTs. In the first, we preferentially alter the direction of the optical photons to increase detection probability. In the second, we follow only a fraction of the total optical photons generated. In both techniques, the statistical weight of photons is altered to maintain the signal mean. We use fastdetect2, an open-source, freely available optical transport routine from the hybridmantis package. We simulate VRTs for a variety of detector models and energy sources. The imaging data from the VRT simulations are then compared to the analog case (no VRT) using pulse height spectra, Swank factor, and the variance of the Swank estimate. We analyze the effect of VRTs on the statistical uncertainty associated with Swank factors. VRTs increased the relative efficiency by as much as a factor of 9. We demonstrate that we can achieve the same variance of the Swank factor with less computing time. With this approach, the simulations can be stopped when the variance of the variance estimates reaches the desired level of uncertainty. We implemented analytic estimates of the variance of Swank factor and demonstrated the effect of VRTs on image quality calculations. Our findings indicate that the Swank factor is dominated by the x-ray interaction profile as compared to the additional uncertainty introduced in the optical transport by the use of VRTs. For simulation experiments that aim at reducing the uncertainty in the Swank factor estimate, any of the proposed VRT can be used for increasing the relative

Variance risk premia in CO_2 markets: A political perspective

International Nuclear Information System (INIS)

Reckling, Dennis

2016-01-01

The European Commission discusses the change of free allocation plans to guarantee a stable market equilibrium. Selling over-allocated contracts effectively depreciates prices and negates the effect intended by the regulator to establish a stable price mechanism for CO_2 assets. Our paper investigates mispricing and allocation issues by quantitatively analyzing variance risk premia of CO_2 markets over the course of changing regimes (Phase I-III) for three different assets (European Union Allowances, Certified Emissions Reductions and European Reduction Units). The research paper gives recommendations to regulatory bodies in order to most effectively cap the overall carbon dioxide emissions. The analysis of an enriched dataset, comprising not only of additional CO_2 assets, but also containing data from the European Energy Exchange, shows that variance risk premia are equal to a sample average of 0.69 for European Union Allowances (EUA), 0.17 for Certified Emissions Reductions (CER) and 0.81 for European Reduction Units (ERU). We identify the existence of a common risk factor across different assets that justifies the presence of risk premia. Various policy implications with regards to gaining investors’ confidence in the market are being reviewed. Consequently, we recommend the implementation of a price collar approach to support stable prices for emission allowances. - Highlights: •Enriched dataset covering all three political phases of the CO_2 markets. •Clear policy implications for regulators to most effectively cap the overall CO_2 emissions pool. •Applying a cross-asset benchmark index for variance beta estimation. •CER contracts have been analyzed with respect to variance risk premia for the first time. •Increased forecasting accuracy for CO_2 asset returns by using variance risk premia.

The genotype-environment interaction variance in rice-seed protein determination

International Nuclear Information System (INIS)

Ismachin, M.

1976-01-01

Many environmental factors influence the protein content of cereal seed. This fact procured difficulties in breeding for protein. Yield is another example on which so many environmental factors are of influence. The length of time required by the plant to reach maturity, is also affected by the environmental factors; even though its effect is not too decisive. In this investigation the genotypic variance and the genotype-environment interaction variance which contribute to the total variance or phenotypic variance was analysed, with purpose to give an idea to the breeder how selection should be made. It was found that genotype-environment interaction variance is larger than the genotypic variance in contribution to total variance of protein-seed determination or yield. In the analysis of the time required to reach maturity it was found that genotypic variance is larger than the genotype-environment interaction variance. It is therefore clear, why selection for time required to reach maturity is much easier than selection for protein or yield. Selected protein in one location may be different from that to other locations. (author)

Estimation of measurement variances

International Nuclear Information System (INIS)

Jaech, J.L.

1984-01-01

The estimation of measurement error parameters in safeguards systems is discussed. Both systematic and random errors are considered. A simple analysis of variances to characterize the measurement error structure with biases varying over time is presented

Ulnar variance: its relationship to ulnar foveal morphology and forearm kinematics.

Science.gov (United States)

Kataoka, Toshiyuki; Moritomo, Hisao; Omokawa, Shohei; Iida, Akio; Murase, Tsuyoshi; Sugamoto, Kazuomi

2012-04-01

It is unclear how individual differences in the anatomy of the distal ulna affect kinematics and pathology of the distal radioulnar joint. This study evaluated how ulnar variance relates to ulnar foveal morphology and the pronosupination axis of the forearm. We performed 3-dimensional computed tomography studies in vivo on 28 forearms in maximum supination and pronation to determine the anatomical center of the ulnar distal pole and the forearm pronosupination axis. We calculated the forearm pronosupination axis using a markerless bone registration technique, which determined the pronosupination center as the point where the axis emerges on the distal ulnar surface. We measured the depth of the anatomical center and classified it into 2 types: concave, with a depth of 0.8 mm or more, and flat, with a depth less than 0.8 mm. We examined whether ulnar variance correlated with foveal type and the distance between anatomical and pronosupination centers. A total of 18 cases had a concave-type fovea surrounded by the C-shaped articular facet of the distal pole, and 10 had a flat-type fovea with a flat surface without evident central depression. Ulnar variance of the flat type was 3.5 ± 1.2 mm, which was significantly greater than the 1.2 ± 1.1 mm of the concave type. Ulnar variance positively correlated with distance between the anatomical and pronosupination centers. Flat-type ulnar heads have a significantly greater ulnar variance than concave types. The pronosupination axis passes through the ulnar head more medially and farther from the anatomical center with increasing ulnar variance. This study suggests that ulnar variance is related in part to foveal morphology and pronosupination axis. This information provides a starting point for future studies investigating how foveal morphology relates to distal ulnar problems. Copyright © 2012 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

29 CFR 1905.5 - Effect of variances.

Science.gov (United States)

2010-07-01

...-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 General § 1905.5 Effect of variances. All variances... Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... concerning a proposed penalty or period of abatement is pending before the Occupational Safety and Health...

Realized range-based estimation of integrated variance

DEFF Research Database (Denmark)

Christensen, Kim; Podolskij, Mark

2007-01-01

We provide a set of probabilistic laws for estimating the quadratic variation of continuous semimartingales with the realized range-based variance-a statistic that replaces every squared return of the realized variance with a normalized squared range. If the entire sample path of the process is a...

Variance Function Partially Linear Single-Index Models1.

Science.gov (United States)

Lian, Heng; Liang, Hua; Carroll, Raymond J

2015-01-01

We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.

Time-dependent, non-monotonic response of warm convective cloud fields to changes in aerosol loading

Directory of Open Access Journals (Sweden)

G. Dagan

2017-06-01

Full Text Available Large eddy simulations (LESs with bin microphysics are used here to study cloud fields' sensitivity to changes in aerosol loading and the time evolution of this response. Similarly to the known response of a single cloud, we show that the mean field properties change in a non-monotonic trend, with an optimum aerosol concentration for which the field reaches its maximal water mass or rain yield. This trend is a result of competition between processes that encourage cloud development versus those that suppress it. However, another layer of complexity is added when considering clouds' impact on the field's thermodynamic properties and how this is dependent on aerosol loading. Under polluted conditions, rain is suppressed and the non-precipitating clouds act to increase atmospheric instability. This results in warming of the lower part of the cloudy layer (in which there is net condensation and cooling of the upper part (net evaporation. Evaporation at the upper part of the cloudy layer in the polluted simulations raises humidity at these levels and thus amplifies the development of the next generation of clouds (preconditioning effect. On the other hand, under clean conditions, the precipitating clouds drive net warming of the cloudy layer and net cooling of the sub-cloud layer due to rain evaporation. These two effects act to stabilize the atmospheric boundary layer with time (consumption of the instability. The evolution of the field's thermodynamic properties affects the cloud properties in return, as shown by the migration of the optimal aerosol concentration toward higher values.

Discrete time and continuous time dynamic mean-variance analysis

OpenAIRE

Reiss, Ariane

1999-01-01

Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...

Variance in exposed perturbations impairs retention of visuomotor adaptation.

Science.gov (United States)

Canaveral, Cesar Augusto; Danion, Frédéric; Berrigan, Félix; Bernier, Pierre-Michel

2017-11-01

Sensorimotor control requires an accurate estimate of the state of the body. The brain optimizes state estimation by combining sensory signals with predictions of the sensory consequences of motor commands using a forward model. Given that both sensory signals and predictions are uncertain (i.e., noisy), the brain optimally weights the relative reliance on each source of information during adaptation. In support, it is known that uncertainty in the sensory predictions influences the rate and generalization of visuomotor adaptation. We investigated whether uncertainty in the sensory predictions affects the retention of a new visuomotor relationship. This was done by exposing three separate groups to a visuomotor rotation whose mean was common at 15° counterclockwise but whose variance around the mean differed (i.e., SD of 0°, 3.2°, or 4.5°). Retention was assessed by measuring the persistence of the adapted behavior in a no-vision phase. Results revealed that mean reach direction late in adaptation was similar across groups, suggesting it depended mainly on the mean of exposed rotations and was robust to differences in variance. However, retention differed across groups, with higher levels of variance being associated with a more rapid reversion toward nonadapted behavior. A control experiment ruled out the possibility that differences in retention were accounted for by differences in success rates. Exposure to variable rotations may have increased the uncertainty in sensory predictions, making the adapted forward model more labile and susceptible to change or decay. NEW & NOTEWORTHY The brain predicts the sensory consequences of motor commands through a forward model. These predictions are subject to uncertainty. We use visuomotor adaptation and modulate uncertainty in the sensory predictions by manipulating the variance in exposed rotations. Results reveal that variance does not influence the final extent of adaptation but selectively impairs the retention of

Expected Stock Returns and Variance Risk Premia

DEFF Research Database (Denmark)

Bollerslev, Tim; Zhou, Hao

risk premium with the P/E ratio results in an R2 for the quarterly returns of more than twenty-five percent. The results depend crucially on the use of "model-free", as opposed to standard Black-Scholes, implied variances, and realized variances constructed from high-frequency intraday, as opposed...

Allowable variance set on left ventricular function parameter

International Nuclear Information System (INIS)

Zhou Li'na; Qi Zhongzhi; Zeng Yu; Ou Xiaohong; Li Lin

2010-01-01

Purpose: To evaluate the influence of allowable Variance settings on left ventricular function parameter of the arrhythmia patients during gated myocardial perfusion imaging. Method: 42 patients with evident arrhythmia underwent myocardial perfusion SPECT, 3 different allowable variance with 20%, 60%, 100% would be set before acquisition for every patients,and they will be acquired simultaneously. After reconstruction by Astonish, end-diastole volume(EDV) and end-systolic volume (ESV) and left ventricular ejection fraction (LVEF) would be computed with Quantitative Gated SPECT(QGS). Using SPSS software EDV, ESV, EF values of analysis of variance. Result: there is no statistical difference between three groups. Conclusion: arrhythmia patients undergo Gated myocardial perfusion imaging, Allowable Variance settings on EDV, ESV, EF value does not have a statistical meaning. (authors)

Deviation of the Variances of Classical Estimators and Negative Integer Moment Estimator from Minimum Variance Bound with Reference to Maxwell Distribution

Directory of Open Access Journals (Sweden)

G. R. Pasha

2006-07-01

Full Text Available In this paper, we present that how much the variances of the classical estimators, namely, maximum likelihood estimator and moment estimator deviate from the minimum variance bound while estimating for the Maxwell distribution. We also sketch this difference for the negative integer moment estimator. We note the poor performance of the negative integer moment estimator in the said consideration while maximum likelihood estimator attains minimum variance bound and becomes an attractive choice.

Towards a mathematical foundation of minimum-variance theory

Energy Technology Data Exchange (ETDEWEB)

Feng Jianfeng [COGS, Sussex University, Brighton (United Kingdom); Zhang Kewei [SMS, Sussex University, Brighton (United Kingdom); Wei Gang [Mathematical Department, Baptist University, Hong Kong (China)

2002-08-30

The minimum-variance theory which accounts for arm and eye movements with noise signal inputs was proposed by Harris and Wolpert (1998 Nature 394 780-4). Here we present a detailed theoretical analysis of the theory and analytical solutions of the theory are obtained. Furthermore, we propose a new version of the minimum-variance theory, which is more realistic for a biological system. For the new version we show numerically that the variance is considerably reduced. (author)

Allowing variance may enlarge the safe operating space for exploited ecosystems

NARCIS (Netherlands)

Carpenter, S.R.; Brock, W.A.; Folke, Carl; Nes, Van E.H.; Scheffer, Marten; Polasky, Stephen

2015-01-01

Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictabilitymay therefore be preferred. However, actions to decrease variance over short timescales (2-4 y), when applied continuously,may lead to

A log-sinh transformation for data normalization and variance stabilization

Science.gov (United States)

Wang, Q. J.; Shrestha, D. L.; Robertson, D. E.; Pokhrel, P.

2012-05-01

When quantifying model prediction uncertainty, it is statistically convenient to represent model errors that are normally distributed with a constant variance. The Box-Cox transformation is the most widely used technique to normalize data and stabilize variance, but it is not without limitations. In this paper, a log-sinh transformation is derived based on a pattern of errors commonly seen in hydrological model predictions. It is suited to applications where prediction variables are positively skewed and the spread of errors is seen to first increase rapidly, then slowly, and eventually approach a constant as the prediction variable becomes greater. The log-sinh transformation is applied in two case studies, and the results are compared with one- and two-parameter Box-Cox transformations.

Direct encoding of orientation variance in the visual system.

Science.gov (United States)

Norman, Liam J; Heywood, Charles A; Kentridge, Robert W

2015-01-01

Our perception of regional irregularity, an example of which is orientation variance, seems effortless when we view two patches of texture that differ in this attribute. Little is understood, however, of how the visual system encodes a regional statistic like orientation variance, but there is some evidence to suggest that it is directly encoded by populations of neurons tuned broadly to high or low levels. The present study shows that selective adaptation to low or high levels of variance results in a perceptual aftereffect that shifts the perceived level of variance of a subsequently viewed texture in the direction away from that of the adapting stimulus (Experiments 1 and 2). Importantly, the effect is durable across changes in mean orientation, suggesting that the encoding of orientation variance is independent of global first moment orientation statistics (i.e., mean orientation). In Experiment 3 it was shown that the variance-specific aftereffect did not show signs of being encoded in a spatiotopic reference frame, similar to the equivalent aftereffect of adaptation to the first moment orientation statistic (the tilt aftereffect), which is represented in the primary visual cortex and exists only in retinotopic coordinates. Experiment 4 shows that a neuropsychological patient with damage to ventral areas of the cortex but spared intact early areas retains sensitivity to orientation variance. Together these results suggest that orientation variance is encoded directly by the visual system and possibly at an early cortical stage.

Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

Science.gov (United States)

Verdery, Ashton M; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J

2015-01-01

This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.

Mean and variance evolutions of the hot and cold temperatures in Europe

Energy Technology Data Exchange (ETDEWEB)

Parey, Sylvie [EDF/R and D, Chatou Cedex (France); Dacunha-Castelle, D. [Universite Paris 11, Laboratoire de Mathematiques, Orsay (France); Hoang, T.T.H. [Universite Paris 11, Laboratoire de Mathematiques, Orsay (France); EDF/R and D, Chatou Cedex (France)

2010-02-15

In this paper, we examine the trends of temperature series in Europe, for the mean as well as for the variance in hot and cold seasons. To do so, we use as long and homogenous series as possible, provided by the European Climate Assessment and Dataset project for different locations in Europe, as well as the European ENSEMBLES project gridded dataset and the ERA40 reanalysis. We provide a definition of trends that we keep as intrinsic as possible and apply non-parametric statistical methods to analyse them. Obtained results show a clear link between trends in mean and variance of the whole series of hot or cold temperatures: in general, variance increases when the absolute value of temperature increases, i.e. with increasing summer temperature and decreasing winter temperature. This link is reinforced in locations where winter and summer climate has more variability. In very cold or very warm climates, the variability is lower and the link between the trends is weaker. We performed the same analysis on outputs of six climate models proposed by European teams for the 1961-2000 period (1950-2000 for one model), available through the PCMDI portal for the IPCC fourth assessment climate model simulations. The models generally perform poorly and have difficulties in capturing the relation between the two trends, especially in summer. (orig.)

Local variances in biomonitoring

International Nuclear Information System (INIS)

Wolterbeek, H.Th; Verburg, T.G.

2001-01-01

The present study was undertaken to explore possibilities to judge survey quality on basis of a limited and restricted number of a-priori observations. Here, quality is defined as the ratio between survey and local variance (signal-to-noise ratio). The results indicate that the presented surveys do not permit such judgement; the discussion also suggests that the 5-fold local sampling strategies do not merit any sound judgement. As it stands, uncertainties in local determinations may largely obscure possibilities to judge survey quality. The results further imply that surveys will benefit from procedures, controls and approaches in sampling and sample handling, to assess both average, variance and the nature of the distribution of elemental concentrations in local sites. This reasoning is compatible with the idea of the site as a basic homogeneous survey unit, which is implicitly and conceptually underlying any survey performed. (author)

Toward a more robust variance-based global sensitivity analysis of model outputs

Energy Technology Data Exchange (ETDEWEB)

Tong, C

2007-10-15

Global sensitivity analysis (GSA) measures the variation of a model output as a function of the variations of the model inputs given their ranges. In this paper we consider variance-based GSA methods that do not rely on certain assumptions about the model structure such as linearity or monotonicity. These variance-based methods decompose the output variance into terms of increasing dimensionality called 'sensitivity indices', first introduced by Sobol' [25]. Sobol' developed a method of estimating these sensitivity indices using Monte Carlo simulations. McKay [13] proposed an efficient method using replicated Latin hypercube sampling to compute the 'correlation ratios' or 'main effects', which have been shown to be equivalent to Sobol's first-order sensitivity indices. Practical issues with using these variance estimators are how to choose adequate sample sizes and how to assess the accuracy of the results. This paper proposes a modified McKay main effect method featuring an adaptive procedure for accuracy assessment and improvement. We also extend our adaptive technique to the computation of second-order sensitivity indices. Details of the proposed adaptive procedure as wells as numerical results are included in this paper.

Refractive variation under accommodative demand: curvital and scaled torsional variances and covariance across the meridians of the eye.

Science.gov (United States)

van Gool, R D; Harris, W F

1997-06-01

Autorefractor measurements were taken on the right eye of 10 students with an external target at vergences -1.00 and -3.00 D. The refractive errors in the form of sphere, cylinder, and axis were converted to vectors h and variance-covariance matrices calculated for different reference meridians. Scatter plots are drawn in symmetric dioptric power space. The profiles of curvital and scaled torsional variances, the scaled torsional fraction, and the scaled torsional-curvital correlation are shown using a polar representation. This form of representation provides a meridional pattern of variation under accommodative demand. The profile for scaled torsional variance is characteristically in the form of a pair of rabbit ears. At both target vergences curvital variance is larger than scaled torsional variance in all the meridians of the eye: the relative magnitudes are quantified by the scaled torsional fraction. An increase in accommodative demand generally results in an increase in variance. The rabbit ears usually become larger but less well divided. The correlation between curvital and torsional powers is usually positive in the first quadrant and negative in the second quadrant. Typical, atypical, and mean typical responses are discussed.

Some variance reduction methods for numerical stochastic homogenization.

Science.gov (United States)

Blanc, X; Le Bris, C; Legoll, F

2016-04-28

We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).

Impact of an equality constraint on the class-specific residual variances in regression mixtures: A Monte Carlo simulation study.

Science.gov (United States)

Kim, Minjung; Lamont, Andrea E; Jaki, Thomas; Feaster, Daniel; Howe, George; Van Horn, M Lee

2016-06-01

Regression mixture models are a novel approach to modeling the heterogeneous effects of predictors on an outcome. In the model-building process, often residual variances are disregarded and simplifying assumptions are made without thorough examination of the consequences. In this simulation study, we investigated the impact of an equality constraint on the residual variances across latent classes. We examined the consequences of constraining the residual variances on class enumeration (finding the true number of latent classes) and on the parameter estimates, under a number of different simulation conditions meant to reflect the types of heterogeneity likely to exist in applied analyses. The results showed that bias in class enumeration increased as the difference in residual variances between the classes increased. Also, an inappropriate equality constraint on the residual variances greatly impacted on the estimated class sizes and showed the potential to greatly affect the parameter estimates in each class. These results suggest that it is important to make assumptions about residual variances with care and to carefully report what assumptions are made.

variance components and genetic parameters for live weight

African Journals Online (AJOL)

admin

Against this background the present study estimated the (co)variance .... Starting values for the (co)variance components of two-trait models were ..... Estimates of genetic parameters for weaning weight of beef accounting for direct-maternal.

Variance Swaps in BM&F: Pricing and Viability of Hedge

Directory of Open Access Journals (Sweden)

Richard John Brostowicz Junior

2010-07-01

Full Text Available A variance swap can theoretically be priced with an infinite set of vanilla calls and puts options considering that the realized variance follows a purely diffusive process with continuous monitoring. In this article we willanalyze the possible differences in pricing considering discrete monitoring of realized variance. It will analyze the pricing of variance swaps with payoff in dollars, since there is a OTC market that works this way and thatpotentially serve as a hedge for the variance swaps traded in BM&F. Additionally, will be tested the feasibility of hedge of variance swaps when there is liquidity in just a few exercise prices, as is the case of FX optionstraded in BM&F. Thus be assembled portfolios containing variance swaps and their replicating portfolios using the available exercise prices as proposed in (DEMETERFI et al., 1999. With these portfolios, the effectiveness of the hedge was not robust in mostly of tests conducted in this work.

Is fMRI "noise" really noise? Resting state nuisance regressors remove variance with network structure.

Science.gov (United States)

Bright, Molly G; Murphy, Kevin

2015-07-01

Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed by 24, 12, 6, or only 3 head motion parameters demonstrated network structure typically associated with functional connectivity, and certain networks were discernable in the variance extracted by as few as 2 physiologic regressors. Simulated nuisance regressors, unrelated to the true data noise, also removed variance with network structure, indicating that any group of regressors that randomly sample variance may remove highly structured "signal" as well as "noise." Furthermore, to support this we demonstrate that random sampling of the original data variance continues to exhibit robust network structure, even when as few as 10% of the original volumes are considered. Finally, we examine the diminishing returns of increasing the number of nuisance regressors used in pre-processing, showing that excessive use of motion regressors may do little better than chance in removing variance within a functional network. It remains an open challenge to understand the balance between the benefits and confounds of noise correction using nuisance regressors. Copyright © 2015. Published by Elsevier Inc.

On the noise variance of a digital mammography system

International Nuclear Information System (INIS)

Burgess, Arthur

2004-01-01

A recent paper by Cooper et al. [Med. Phys. 30, 2614-2621 (2003)] contains some apparently anomalous results concerning the relationship between pixel variance and x-ray exposure for a digital mammography system. They found an unexpected peak in a display domain pixel variance plot as a function of 1/mAs (their Fig. 5) with a decrease in the range corresponding to high display data values, corresponding to low x-ray exposures. As they pointed out, if the detector response is linear in exposure and the transformation from raw to display data scales is logarithmic, then pixel variance should be a monotonically increasing function in the figure. They concluded that the total system transfer curve, between input exposure and display image data values, is not logarithmic over the full exposure range. They separated data analysis into two regions and plotted the logarithm of display image pixel variance as a function of the logarithm of the mAs used to produce the phantom images. They found a slope of minus one for high mAs values and concluded that the transfer function is logarithmic in this region. They found a slope of 0.6 for the low mAs region and concluded that the transfer curve was neither linear nor logarithmic for low exposure values. It is known that the digital mammography system investigated by Cooper et al. has a linear relationship between exposure and raw data values [Vedantham et al., Med. Phys. 27, 558-567 (2000)]. The purpose of this paper is to show that the variance effect found by Cooper et al. (their Fig. 5) arises because the transformation from the raw data scale (14 bits) to the display scale (12 bits), for the digital mammography system they investigated, is not logarithmic for raw data values less than about 300 (display data values greater than about 3300). At low raw data values the transformation is linear and prevents over-ranging of the display data scale. Parametric models for the two transformations will be presented. Results of pixel

Integrating mean and variance heterogeneities to identify differentially expressed genes.

Science.gov (United States)

Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

2016-12-06

In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

Simultaneous Monte Carlo zero-variance estimates of several correlated means

International Nuclear Information System (INIS)

Booth, T.E.

1998-01-01

Zero-variance biasing procedures are normally associated with estimating a single mean or tally. In particular, a zero-variance solution occurs when every sampling is made proportional to the product of the true probability multiplied by the expected score (importance) subsequent to the sampling; i.e., the zero-variance sampling is importance weighted. Because every tally has a different importance function, a zero-variance biasing for one tally cannot be a zero-variance biasing for another tally (unless the tallies are perfectly correlated). The way to optimize the situation when the required tallies have positive correlation is shown

Comparing estimates of genetic variance across different relationship models.

Science.gov (United States)

Legarra, Andres

2016-02-01

Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

Variance computations for functional of absolute risk estimates.

Science.gov (United States)

Pfeiffer, R M; Petracci, E

2011-07-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

76 FR 78698 - Proposed Revocation of Permanent Variances

Science.gov (United States)

2011-12-19

... Administration (``OSHA'' or ``the Agency'') granted permanent variances to 24 companies engaged in the... DEPARTMENT OF LABOR Occupational Safety and Health Administration [Docket No. OSHA-2011-0054] Proposed Revocation of Permanent Variances AGENCY: Occupational Safety and Health Administration (OSHA...

Canonical single field slow-roll inflation with a non-monotonic tensor-to-scalar ratio

Energy Technology Data Exchange (ETDEWEB)

Germán, Gabriel [Rudolf Peierls Centre for Theoretical Physics, University of Oxford, 1 Keble Road, Oxford, OX1 3NP (United Kingdom); Herrera-Aguilar, Alfredo [Instituto de Física, Benemérita Universidad Autónoma de Puebla, Apdo. postal J-48, CP 72570, Puebla, Pue., México (Mexico); Hidalgo, Juan Carlos [Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Apdo. postal 48-3, 62251 Cuernavaca, Morelos, México (Mexico); Sussman, Roberto A., E-mail: gabriel@fis.unam.mx, E-mail: aherrera@ifuap.buap.mx, E-mail: hidalgo@fis.unam.mx, E-mail: sussman@nucleares.unam.mx [Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Apdo. postal 70-543, 04510 México D. F., México (Mexico)

2016-05-01

We take a pragmatic, model independent approach to single field slow-roll canonical inflation by imposing conditions, not on the potential, but on the slow-roll parameter ε(φ) and its derivatives ε'(φ) and ε''(φ), thereby extracting general conditions on the tensor-to-scalar ratio r and the running n {sub sk} at φ {sub H} where the perturbations are produced, some 50–60 e -folds before the end of inflation. We find quite generally that for models where ε(φ) develops a maximum, a relatively large r is most likely accompanied by a positive running while a negligible tensor-to-scalar ratio implies negative running. The definitive answer, however, is given in terms of the slow-roll parameter ξ{sub 2}(φ). To accommodate a large tensor-to-scalar ratio that meets the limiting values allowed by the Planck data, we study a non-monotonic ε(φ) decreasing during most part of inflation. Since at φ {sub H} the slow-roll parameter ε(φ) is increasing, we thus require that ε(φ) develops a maximum for φ > φ {sub H} after which ε(φ) decrease to small values where most e -folds are produced. The end of inflation might occur trough a hybrid mechanism and a small field excursion Δφ {sub e} ≡ |φ {sub H} −φ {sub e} | is obtained with a sufficiently thin profile for ε(φ) which, however, should not conflict with the second slow-roll parameter η(φ). As a consequence of this analysis we find bounds for Δφ {sub e} , r {sub H} and for the scalar spectral index n {sub sH} . Finally we provide examples where these considerations are explicitly realised.

Diagnostic checking in linear processes with infinit variance

OpenAIRE

Krämer, Walter; Runde, Ralf

1998-01-01

We consider empirical autocorrelations of residuals from infinite variance autoregressive processes. Unlike the finite-variance case, it emerges that the limiting distribution, after suitable normalization, is not always more concentrated around zero when residuals rather than true innovations are employed.

Search for scalar-tensor gravity theories with a non-monotonic time evolution of the speed-up factor

Energy Technology Data Exchange (ETDEWEB)

Navarro, A [Dept Fisica, Universidad de Murcia, E30071-Murcia (Spain); Serna, A [Dept Fisica, Computacion y Comunicaciones, Universidad Miguel Hernandez, E03202-Elche (Spain); Alimi, J-M [Lab. de l' Univers et de ses Theories (LUTH, CNRS FRE2462), Observatoire de Paris-Meudon, F92195-Meudon (France)

2002-08-21

We present a method to detect, in the framework of scalar-tensor gravity theories, the existence of stationary points in the time evolution of the speed-up factor. An attractive aspect of this method is that, once the particular scalar-tensor theory has been specified, the stationary points are found through a simple algebraic equation which does not contain any integration. By applying this method to the three classes of scalar-tensor theories defined by Barrow and Parsons, we have found several new cosmological models with a non-monotonic evolution of the speed-up factor. The physical interest of these models is that, as previously shown by Serna and Alimi, they predict the observed primordial abundance of light elements for a very wide range of baryon density. These models are then consistent with recent CMB and Lyman-{alpha} estimates of the baryon content of the universe.

RR-Interval variance of electrocardiogram for atrial fibrillation detection

Science.gov (United States)

Nuryani, N.; Solikhah, M.; Nugoho, A. S.; Afdala, A.; Anzihory, E.

2016-11-01

Atrial fibrillation is a serious heart problem originated from the upper chamber of the heart. The common indication of atrial fibrillation is irregularity of R peak-to-R-peak time interval, which is shortly called RR interval. The irregularity could be represented using variance or spread of RR interval. This article presents a system to detect atrial fibrillation using variances. Using clinical data of patients with atrial fibrillation attack, it is shown that the variance of electrocardiographic RR interval are higher during atrial fibrillation, compared to the normal one. Utilizing a simple detection technique and variances of RR intervals, we find a good performance of atrial fibrillation detection.

Continuous-Time Mean-Variance Portfolio Selection under the CEV Process

OpenAIRE

Ma, Hui-qiang

2014-01-01

We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV) process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance effici...

Variance based OFDM frame synchronization

Directory of Open Access Journals (Sweden)

Z. Fedra

2012-04-01

Full Text Available The paper deals with a new frame synchronization scheme for OFDM systems and calculates the complexity of this scheme. The scheme is based on the computing of the detection window variance. The variance is computed in two delayed times, so a modified Early-Late loop is used for the frame position detection. The proposed algorithm deals with different variants of OFDM parameters including guard interval, cyclic prefix, and has good properties regarding the choice of the algorithm's parameters since the parameters may be chosen within a wide range without having a high influence on system performance. The verification of the proposed algorithm functionality has been performed on a development environment using universal software radio peripheral (USRP hardware.

Means and Variances without Calculus

Science.gov (United States)

Kinney, John J.

2005-01-01

This article gives a method of finding discrete approximations to continuous probability density functions and shows examples of its use, allowing students without calculus access to the calculation of means and variances.

Non-monotonic swelling of surface grafted hydrogels induced by pH and/or salt concentration

Science.gov (United States)

Longo, Gabriel S.; Olvera de la Cruz, Monica; Szleifer, I.

2014-09-01

We use a molecular theory to study the thermodynamics of a weak-polyacid hydrogel film that is chemically grafted to a solid surface. We investigate the response of the material to changes in the pH and salt concentration of the buffer solution. Our results show that the pH-triggered swelling of the hydrogel film has a non-monotonic dependence on the acidity of the bath solution. At most salt concentrations, the thickness of the hydrogel film presents a maximum when the pH of the solution is increased from acidic values. The quantitative details of such swelling behavior, which is not observed when the film is physically deposited on the surface, depend on the molecular architecture of the polymer network. This swelling-deswelling transition is the consequence of the complex interplay between the chemical free energy (acid-base equilibrium), the electrostatic repulsions between charged monomers, which are both modulated by the absorption of ions, and the ability of the polymer network to regulate charge and control its volume (molecular organization). In the absence of such competition, for example, for high salt concentrations, the film swells monotonically with increasing pH. A deswelling-swelling transition is similarly predicted as a function of the salt concentration at intermediate pH values. This reentrant behavior, which is due to the coupling between charge regulation and the two opposing effects triggered by salt concentration (screening electrostatic interactions and charging/discharging the acid groups), is similar to that found in end-grafted weak polyelectrolyte layers. Understanding how to control the response of the material to different stimuli, in terms of its molecular structure and local chemical composition, can help the targeted design of applications with extended functionality. We describe the response of the material to an applied pressure and an electric potential. We present profiles that outline the local chemical composition of the

Evaluation of Mean and Variance Integrals without Integration

Science.gov (United States)

Joarder, A. H.; Omar, M. H.

2007-01-01

The mean and variance of some continuous distributions, in particular the exponentially decreasing probability distribution and the normal distribution, are considered. Since they involve integration by parts, many students do not feel comfortable. In this note, a technique is demonstrated for deriving mean and variance through differential…

Empirical single sample quantification of bias and variance in Q-ball imaging.

Science.gov (United States)

Hainline, Allison E; Nath, Vishwesh; Parvathaneni, Prasanna; Blaber, Justin A; Schilling, Kurt G; Anderson, Adam W; Kang, Hakmook; Landman, Bennett A

2018-02-06

The bias and variance of high angular resolution diffusion imaging methods have not been thoroughly explored in the literature and may benefit from the simulation extrapolation (SIMEX) and bootstrap techniques to estimate bias and variance of high angular resolution diffusion imaging metrics. The SIMEX approach is well established in the statistics literature and uses simulation of increasingly noisy data to extrapolate back to a hypothetical case with no noise. The bias of calculated metrics can then be computed by subtracting the SIMEX estimate from the original pointwise measurement. The SIMEX technique has been studied in the context of diffusion imaging to accurately capture the bias in fractional anisotropy measurements in DTI. Herein, we extend the application of SIMEX and bootstrap approaches to characterize bias and variance in metrics obtained from a Q-ball imaging reconstruction of high angular resolution diffusion imaging data. The results demonstrate that SIMEX and bootstrap approaches provide consistent estimates of the bias and variance of generalized fractional anisotropy, respectively. The RMSE for the generalized fractional anisotropy estimates shows a 7% decrease in white matter and an 8% decrease in gray matter when compared with the observed generalized fractional anisotropy estimates. On average, the bootstrap technique results in SD estimates that are approximately 97% of the true variation in white matter, and 86% in gray matter. Both SIMEX and bootstrap methods are flexible, estimate population characteristics based on single scans, and may be extended for bias and variance estimation on a variety of high angular resolution diffusion imaging metrics. © 2018 International Society for Magnetic Resonance in Medicine.

Numerical simulation of variance of solar radiation and its influence on wheat growth

Science.gov (United States)

Zhang, Xuefen; Wang, Chunyi; Du, Zixuan; Zhai, Wei

2007-09-01

The growth of crops is directly related to solar radiation whose variances influence the photosynthesis of crops and the growth momentum thereof. This dissertation has Zhengzhou, which located in the Huanghuai Farmland Ecological System of China, as an example to analyze the rules of variances of total solar radiation, direct radiation and diffusive radiation. With the help of linear trend fitting, it is identified that total radiation (TR) drops as a whole at a rate of 1.6482J/m2. Such drop has been particularly apparent in recent years with a period of 7 to 16 years; diffusive radiation (DF) tends to increase at a rate of 15.149 J/m2 with a period of 20 years; direct radiation (DR) tends to drop at a rate of 15.843 J/m2 without apparent period. The total radiation has been on the decrease ever since 1980 during the growth period of wheat. Having modified relevant Parameter in the Carbon and Nitrogen Biogeochemistry in Agroecosystems Model (DNDC) model and simulated the influence of solar radiation variances on the development phase, leaf area index (LAI), grain weight, etc during the growth period of wheat, it is found that solar radiation is in positive proportion to LAI and grain weight (GRNWT) but not apparently related to development phase (DP). The change of total radiation delays the maximization of wheat LAI, reduces wheat LAI before winter but has no apparent effect in winter and decreases wheat LAI from jointing period to filling period; it has no apparent influence on grain formation at the early stage of grain formation, slows down the weight increase of grains during the filling period and accelerates the weight increase of grains at the end of filling period. Variance of radiations does not affect the DP of wheat much.

Variance in binary stellar population synthesis

Science.gov (United States)

Breivik, Katelyn; Larson, Shane L.

2016-03-01

In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations in less than a week, thus allowing a full exploration of the variance associated with a binary stellar evolution model.

The influence of mean climate trends and climate variance on beaver survival and recruitment dynamics.

Science.gov (United States)

Campbell, Ruairidh D; Nouvellet, Pierre; Newman, Chris; Macdonald, David W; Rosell, Frank

2012-09-01

Ecologists are increasingly aware of the importance of environmental variability in natural systems. Climate change is affecting both the mean and the variability in weather and, in particular, the effect of changes in variability is poorly understood. Organisms are subject to selection imposed by both the mean and the range of environmental variation experienced by their ancestors. Changes in the variability in a critical environmental factor may therefore have consequences for vital rates and population dynamics. Here, we examine ≥90-year trends in different components of climate (precipitation mean and coefficient of variation (CV); temperature mean, seasonal amplitude and residual variance) and consider the effects of these components on survival and recruitment in a population of Eurasian beavers (n = 242) over 13 recent years. Within climatic data, no trends in precipitation were detected, but trends in all components of temperature were observed, with mean and residual variance increasing and seasonal amplitude decreasing over time. A higher survival rate was linked (in order of influence based on Akaike weights) to lower precipitation CV (kits, juveniles and dominant adults), lower residual variance of temperature (dominant adults) and lower mean precipitation (kits and juveniles). No significant effects were found on the survival of nondominant adults, although the sample size for this category was low. Greater recruitment was linked (in order of influence) to higher seasonal amplitude of temperature, lower mean precipitation, lower residual variance in temperature and higher precipitation CV. Both climate means and variance, thus proved significant to population dynamics; although, overall, components describing variance were more influential than those describing mean values. That environmental variation proves significant to a generalist, wide-ranging species, at the slow end of the slow-fast continuum of life histories, has broad implications for

Is fMRI “noise” really noise? Resting state nuisance regressors remove variance with network structure

Science.gov (United States)

Bright, Molly G.; Murphy, Kevin

2015-01-01

Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed by 24, 12, 6, or only 3 head motion parameters demonstrated network structure typically associated with functional connectivity, and certain networks were discernable in the variance extracted by as few as 2 physiologic regressors. Simulated nuisance regressors, unrelated to the true data noise, also removed variance with network structure, indicating that any group of regressors that randomly sample variance may remove highly structured “signal” as well as “noise.” Furthermore, to support this we demonstrate that random sampling of the original data variance continues to exhibit robust network structure, even when as few as 10% of the original volumes are considered. Finally, we examine the diminishing returns of increasing the number of nuisance regressors used in pre-processing, showing that excessive use of motion regressors may do little better than chance in removing variance within a functional network. It remains an open challenge to understand the balance between the benefits and confounds of noise correction using nuisance regressors. PMID:25862264

Seizing an opportunity: increasing use of cessation services following a tobacco tax increase.

Science.gov (United States)

Keller, Paula A; Greenseid, Lija O; Christenson, Matthew; Boyle, Raymond G; Schillo, Barbara A

2015-04-10

Tobacco tax increases are associated with increases in quitline calls and reductions in smoking prevalence. In 2013, ClearWay Minnesota(SM) conducted a six-week media campaign promoting QUITPLAN® Services (QUITPLAN Helpline and quitplan.com) to leverage the state's tax increase. The purpose of this study was to ascertain the association of the tax increase and media campaign on call volumes, web visits, and enrollments in QUITPLAN Services. In this observational study, call volume, web visits, enrollments, and participant characteristics were analyzed for the periods June-August 2012 and June-August 2013. Enrollment data and information about media campaigns were analyzed using multivariate regression analysis to determine the association of the tax increase on QUITPLAN Services while controlling for media. There was a 160% increase in total combined calls and web visits, and an 81% increase in enrollments in QUITPLAN Services. Helpline call volumes and enrollments declined back to prior year levels approximately six weeks after the tax increase. Visits to and enrollments in quitplan.com also declined, but increased again in mid-August. The tax increase and media explained over 70% of variation in enrollments in the QUITPLAN Helpline, with media explaining 34% of the variance and the tax increase explaining an additional 36.1% of this variance. However, media explained 64% of the variance in quitplan.com enrollments, and the tax increase explained an additional 7.6% of this variance. Since tax increases occur infrequently, these policy changes must be fully leveraged as quickly as possible to help reduce prevalence.

A Mean variance analysis of arbitrage portfolios

Science.gov (United States)

Fang, Shuhong

2007-03-01

Based on the careful analysis of the definition of arbitrage portfolio and its return, the author presents a mean-variance analysis of the return of arbitrage portfolios, which implies that Korkie and Turtle's results ( B. Korkie, H.J. Turtle, A mean-variance analysis of self-financing portfolios, Manage. Sci. 48 (2002) 427-443) are misleading. A practical example is given to show the difference between the arbitrage portfolio frontier and the usual portfolio frontier.

Mean-Variance Optimization in Markov Decision Processes

OpenAIRE

Mannor, Shie; Tsitsiklis, John N.

2011-01-01

We consider finite horizon Markov decision processes under performance measures that involve both the mean and the variance of the cumulative reward. We show that either randomized or history-based policies can improve performance. We prove that the complexity of computing a policy that maximizes the mean reward under a variance constraint is NP-hard for some cases, and strongly NP-hard for others. We finally offer pseudo-polynomial exact and approximation algorithms.

Gender Variance and Educational Psychology: Implications for Practice

Science.gov (United States)

Yavuz, Carrie

2016-01-01

The area of gender variance appears to be more visible in both the media and everyday life. Within educational psychology literature gender variance remains underrepresented. The positioning of educational psychologists working across the three levels of child and family, school or establishment and education authority/council, means that they are…

Variance-in-Mean Effects of the Long Forward-Rate Slope

DEFF Research Database (Denmark)

Christiansen, Charlotte

2005-01-01

This paper contains an empirical analysis of the dependence of the long forward-rate slope on the long-rate variance. The long forward-rate slope and the long rate are described by a bivariate GARCH-in-mean model. In accordance with theory, a negative long-rate variance-in-mean effect for the long...... forward-rate slope is documented. Thus, the greater the long-rate variance, the steeper the long forward-rate curve slopes downward (the long forward-rate slope is negative). The variance-in-mean effect is both statistically and economically significant....

Genetic control of residual variance of yearling weight in nellore beef cattle

NARCIS (Netherlands)

Iung, L.H.S.; Neves, H.H.R.; Mulder, H.A.; Carvalheiro, R.

2017-01-01

There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between

Variance-based sensitivity indices for models with dependent inputs

International Nuclear Information System (INIS)

Mara, Thierry A.; Tarantola, Stefano

2012-01-01

Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.

Simultaneous Monte Carlo zero-variance estimates of several correlated means

International Nuclear Information System (INIS)

Booth, T.E.

1997-08-01

Zero variance procedures have been in existence since the dawn of Monte Carlo. Previous works all treat the problem of zero variance solutions for a single tally. One often wants to get low variance solutions to more than one tally. When the sets of random walks needed for two tallies are similar, it is more efficient to do zero variance biasing for both tallies in the same Monte Carlo run, instead of two separate runs. The theory presented here correlates the random walks of particles by the similarity of their tallies. Particles with dissimilar tallies rapidly become uncorrelated whereas particles with similar tallies will stay correlated through most of their random walk. The theory herein should allow practitioners to make efficient use of zero-variance biasing procedures in practical problems

The value of travel time variance

DEFF Research Database (Denmark)

Fosgerau, Mogens; Engelson, Leonid

2011-01-01

This paper considers the value of travel time variability under scheduling preferences that are defined in terms of linearly time varying utility rates associated with being at the origin and at the destination. The main result is a simple expression for the value of travel time variability...... that does not depend on the shape of the travel time distribution. The related measure of travel time variability is the variance of travel time. These conclusions apply equally to travellers who can freely choose departure time and to travellers who use a scheduled service with fixed headway. Depending...... on parameters, travellers may be risk averse or risk seeking and the value of travel time may increase or decrease in the mean travel time....

Variance swap payoffs, risk premia and extreme market conditions

DEFF Research Database (Denmark)

Rombouts, Jeroen V.K.; Stentoft, Lars; Violante, Francesco

This paper estimates the Variance Risk Premium (VRP) directly from synthetic variance swap payoffs. Since variance swap payoffs are highly volatile, we extract the VRP by using signal extraction techniques based on a state-space representation of our model in combination with a simple economic....... The latter variables and the VRP generate different return predictability on the major US indices. A factor model is proposed to extract a market VRP which turns out to be priced when considering Fama and French portfolios....

Estimating quadratic variation using realized variance

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Shephard, N.

2002-01-01

with a rather general SV model - which is a special case of the semimartingale model. Then QV is integrated variance and we can derive the asymptotic distribution of the RV and its rate of convergence. These results do not require us to specify a model for either the drift or volatility functions, although we...... have to impose some weak regularity assumptions. We illustrate the use of the limit theory on some exchange rate data and some stock data. We show that even with large values of M the RV is sometimes a quite noisy estimator of integrated variance. Copyright © 2002 John Wiley & Sons, Ltd....

Meditations on birth weight: is it better to reduce the variance or increase the mean?

Science.gov (United States)

Haig, David

2003-07-01

A conceptual model is presented here in which the birth weight distribution is decomposed into a distribution of target weights and a distribution of perturbations from the target. The target weight is the adaptive goal of fetal development. In the simplest model, perinatal mortality is independent of variation in target weight and determined solely by the magnitude of the perturbation of birth weight from the target. In this model, mortality risk is concentrated in the tails of the birth weight distribution. A difference between populations in their distributions of target weights will be associated with a corresponding shift in their curves of weight-specific risk, without any difference between the populations in overall risk. In this model, risk would be reduced by decreasing the variance of the distribution of perturbations. The model is discussed in the context of the so-called "paradoxes of low birth weight."

Dynamics of Variance Risk Premia, Investors' Sentiment and Return Predictability

DEFF Research Database (Denmark)

Rombouts, Jerome V.K.; Stentoft, Lars; Violante, Francesco

We develop a joint framework linking the physical variance and its risk neutral expectation implying variance risk premia that are persistent, appropriately reacting to changes in level and variability of the variance and naturally satisfying the sign constraint. Using option market data and real...... events and only marginally by the premium associated with normal price fluctuations....

A note on minimum-variance theory and beyond

Energy Technology Data Exchange (ETDEWEB)

Feng Jianfeng [Department of Informatics, Sussex University, Brighton, BN1 9QH (United Kingdom); Tartaglia, Giangaetano [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy); Tirozzi, Brunello [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy)

2004-04-30

We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons.

A note on minimum-variance theory and beyond

International Nuclear Information System (INIS)

Feng Jianfeng; Tartaglia, Giangaetano; Tirozzi, Brunello

2004-01-01

We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons

Genetic variance for uniformity of harvest weight in Nile tilapia (Oreochromis niloticus)

NARCIS (Netherlands)

Khaw, H.L.; Ponzoni, R.W.; Yee, H.Y.; Aziz, M.A.; Mulder, H.A.; Marjanovic, J.; Bijma, P.

2016-01-01

Competition for resources is common in aquaculture, which inflates the variability of fish body weight. Selective breeding is one of the effective approaches that may enable a reduction of size variability (or increase in uniformity) for body weight by genetic means. The genetic variance of

Energy and variance budgets of a diffusive staircase with implications for heat flux scaling

Science.gov (United States)

Hieronymus, M.; Carpenter, J. R.

2016-02-01

Diffusive convection, the mode of double-diffusive convection that occur when both temperature and salinity increase with increasing depth, is commonplace throughout the high latitude oceans and diffusive staircases constitute an important heat transport process in the Arctic Ocean. Heat and buoyancy fluxes through these staircases are often estimated using flux laws deduced either from laboratory experiments, or from simplified energy or variance budgets. We have done direct numerical simulations of double-diffusive convection at a range of Rayleigh numbers and quantified the energy and variance budgets in detail. This allows us to compare the fluxes in our simulations to those derived using known flux laws and to quantify how well the simplified energy and variance budgets approximate the full budgets. The fluxes are found to agree well with earlier estimates at high Rayleigh numbers, but we find large deviations at low Rayleigh numbers. The close ties between the heat and buoyancy fluxes and the budgets of thermal variance and energy have been utilized to derive heat flux scaling laws in the field of thermal convection. The result is the so called GL-theory, which has been found to give accurate heat flux scaling laws in a very wide parameter range. Diffusive convection has many similarities to thermal convection and an extension of the GL-theory to diffusive convection is also presented and its predictions are compared to the results from our numerical simulations.

Estimating High-Frequency Based (Co-) Variances: A Unified Approach

DEFF Research Database (Denmark)

Voev, Valeri; Nolte, Ingmar

We propose a unified framework for estimating integrated variances and covariances based on simple OLS regressions, allowing for a general market microstructure noise specification. We show that our estimators can outperform, in terms of the root mean squared error criterion, the most recent...... and commonly applied estimators, such as the realized kernels of Barndorff-Nielsen, Hansen, Lunde & Shephard (2006), the two-scales realized variance of Zhang, Mykland & Aït-Sahalia (2005), the Hayashi & Yoshida (2005) covariance estimator, and the realized variance and covariance with the optimal sampling...

Interacting opinion and disease dynamics in multiplex networks: Discontinuous phase transition and nonmonotonic consensus times

Science.gov (United States)

Velásquez-Rojas, Fátima; Vazquez, Federico

2017-05-01

Opinion formation and disease spreading are among the most studied dynamical processes on complex networks. In real societies, it is expected that these two processes depend on and affect each other. However, little is known about the effects of opinion dynamics over disease dynamics and vice versa, since most studies treat them separately. In this work we study the dynamics of the voter model for opinion formation intertwined with that of the contact process for disease spreading, in a population of agents that interact via two types of connections, social and contact. These two interacting dynamics take place on two layers of networks, coupled through a fraction q of links present in both networks. The probability that an agent updates its state depends on both the opinion and disease states of the interacting partner. We find that the opinion dynamics has striking consequences on the statistical properties of disease spreading. The most important is that the smooth (continuous) transition from a healthy to an endemic phase observed in the contact process, as the infection probability increases beyond a threshold, becomes abrupt (discontinuous) in the two-layer system. Therefore, disregarding the effects of social dynamics on epidemics propagation may lead to a misestimation of the real magnitude of the spreading. Also, an endemic-healthy discontinuous transition is found when the coupling q overcomes a threshold value. Furthermore, we show that the disease dynamics delays the opinion consensus, leading to a consensus time that varies nonmonotonically with q in a large range of the model's parameters. A mean-field approach reveals that the coupled dynamics of opinions and disease can be approximately described by the dynamics of the voter model decoupled from that of the contact process, with effective probabilities of opinion and disease transmission.

A CLASS OF NONMONOTONE TRUST REGION ALGORITHMS FOR LINEARLY CONSTRAINED OPTIMIZATION%线性约束优化的一类非单调信赖域算法

Institute of Scientific and Technical Information of China (English)

葛恒武; 陈中文

2002-01-01

We present a class of nonmonotone trust region algorithms for linearly constrained optimization in this paper.The algorithm may adjust automatically the scope of the monotonicity by the degree that the quadratic model is "trusted".Under the suitable conditions,it is proved that any limit point of the infinite sequence generated by the algorithm is the Kuhn-Tucker point of the primal problem.Finally,some numerical results show that the new algorithm is very effective.

The Genealogical Consequences of Fecundity Variance Polymorphism

Science.gov (United States)

Taylor, Jesse E.

2009-01-01

The genealogical consequences of within-generation fecundity variance polymorphism are studied using coalescent processes structured by genetic backgrounds. I show that these processes have three distinctive features. The first is that the coalescent rates within backgrounds are not jointly proportional to the infinitesimal variance, but instead depend only on the frequencies and traits of genotypes containing each allele. Second, the coalescent processes at unlinked loci are correlated with the genealogy at the selected locus; i.e., fecundity variance polymorphism has a genomewide impact on genealogies. Third, in diploid models, there are infinitely many combinations of fecundity distributions that have the same diffusion approximation but distinct coalescent processes; i.e., in this class of models, ancestral processes and allele frequency dynamics are not in one-to-one correspondence. Similar properties are expected to hold in models that allow for heritable variation in other traits that affect the coalescent effective population size, such as sex ratio or fecundity and survival schedules. PMID:19433628

An apparent contradiction: increasing variability to achieve greater precision?

Science.gov (United States)

Rosenblatt, Noah J; Hurt, Christopher P; Latash, Mark L; Grabiner, Mark D

2014-02-01

To understand the relationship between variability of foot placement in the frontal plane and stability of gait patterns, we explored how constraining mediolateral foot placement during walking affects the structure of kinematic variance in the lower-limb configuration space during the swing phase of gait. Ten young subjects walked under three conditions: (1) unconstrained (normal walking), (2) constrained (walking overground with visual guides for foot placement to achieve the measured unconstrained step width) and, (3) beam (walking on elevated beams spaced to achieve the measured unconstrained step width). The uncontrolled manifold analysis of the joint configuration variance was used to quantify two variance components, one that did not affect the mediolateral trajectory of the foot in the frontal plane ("good variance") and one that affected this trajectory ("bad variance"). Based on recent studies, we hypothesized that across conditions (1) the index of the synergy stabilizing the mediolateral trajectory of the foot (the normalized difference between the "good variance" and "bad variance") would systematically increase and (2) the changes in the synergy index would be associated with a disproportionate increase in the "good variance." Both hypotheses were confirmed. We conclude that an increase in the "good variance" component of the joint configuration variance may be an effective method of ensuring high stability of gait patterns during conditions requiring increased control of foot placement, particularly if a postural threat is present. Ultimately, designing interventions that encourage a larger amount of "good variance" may be a promising method of improving stability of gait patterns in populations such as older adults and neurological patients.

Extending i-line capabilities through variance characterization and tool enhancement

Science.gov (United States)

Miller, Dan; Salinas, Adrian; Peterson, Joel; Vickers, David; Williams, Dan

2006-03-01

Continuous economic pressures have moved a large percent of integrated device manufacturing (IDM) operations either overseas or to foundry operations over the last 10 years. These pressures have left the IDM fabs in the U.S. with required COO improvements in order to maintain operations domestically. While the assets of many of these factories are at a very favorable point in the depreciation life cycle, the equipment and processes are constrained to the quality of the equipment in its original state and the degradation over its installed life. With the objective to enhance output and improve process performance, this factory and their primary lithography process tool supplier have been able to extend the usable life of the existing process tools, increase the output of the tool base, and improve the distribution of the CDs on the product produced. Texas Instruments Incorporated lead an investigation with the POLARIS ® Systems & Services business of FSI International to determine the sources of variance in the i-line processing of a wide array of IC device types. Data from the sources of variance were investigated such as PEB temp, PEB delay time, develop recipe, develop time, and develop programming. While PEB processes are a primary driver of acid catalyzed resists, the develop mode is shown in this work to have an overwhelming impact on the wafer to wafer and across wafer CD performance of these i-line processes. These changes have been able to improve the wafer to wafer CD distribution by more than 80 %, and the within wafer CD distribution by more than 50 % while enabling a greater than 50 % increase in lithography cluster throughput. The paper will discuss the contribution from each of the sources of variance and their importance in overall system performance.

On Mean-Variance Analysis

OpenAIRE

Li, Yang; Pirvu, Traian A

2011-01-01

This paper considers the mean variance portfolio management problem. We examine portfolios which contain both primary and derivative securities. The challenge in this context is due to portfolio's nonlinearities. The delta-gamma approximation is employed to overcome it. Thus, the optimization problem is reduced to a well posed quadratic program. The methodology developed in this paper can be also applied to pricing and hedging in incomplete markets.

Modelling volatility by variance decomposition

DEFF Research Database (Denmark)

Amado, Cristina; Teräsvirta, Timo

In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the condit...

Variance heterogeneity in Saccharomyces cerevisiae expression data: trans-regulation and epistasis.

Science.gov (United States)

Nelson, Ronald M; Pettersson, Mats E; Li, Xidan; Carlborg, Örjan

2013-01-01

Here, we describe the results from the first variance heterogeneity Genome Wide Association Study (VGWAS) on yeast expression data. Using this forward genetics approach, we show that the genetic regulation of gene-expression in the budding yeast, Saccharomyces cerevisiae, includes mechanisms that can lead to variance heterogeneity in the expression between genotypes. Additionally, we performed a mean effect association study (GWAS). Comparing the mean and variance heterogeneity analyses, we find that the mean expression level is under genetic regulation from a larger absolute number of loci but that a higher proportion of the variance controlling loci were trans-regulated. Both mean and variance regulating loci cluster in regulatory hotspots that affect a large number of phenotypes; a single variance-controlling locus, mapping close to DIA2, was found to be involved in more than 10% of the significant associations. It has been suggested in the literature that variance-heterogeneity between the genotypes might be due to genetic interactions. We therefore screened the multi-locus genotype-phenotype maps for several traits where multiple associations were found, for indications of epistasis. Several examples of two and three locus genetic interactions were found to involve variance-controlling loci, with reports from the literature corroborating the functional connections between the loci. By using a new analytical approach to re-analyze a powerful existing dataset, we are thus able to both provide novel insights to the genetic mechanisms involved in the regulation of gene-expression in budding yeast and experimentally validate epistasis as an important mechanism underlying genetic variance-heterogeneity between genotypes.

Genetic Variance in Homophobia: Evidence from Self- and Peer Reports.

Science.gov (United States)

Zapko-Willmes, Alexandra; Kandler, Christian

2018-01-01

The present twin study combined self- and peer assessments of twins' general homophobia targeting gay men in order to replicate previous behavior genetic findings across different rater perspectives and to disentangle self-rater-specific variance from common variance in self- and peer-reported homophobia (i.e., rater-consistent variance). We hypothesized rater-consistent variance in homophobia to be attributable to genetic and nonshared environmental effects, and self-rater-specific variance to be partially accounted for by genetic influences. A sample of 869 twins and 1329 peer raters completed a seven item scale containing cognitive, affective, and discriminatory homophobic tendencies. After correction for age and sex differences, we found most of the genetic contributions (62%) and significant nonshared environmental contributions (16%) to individual differences in self-reports on homophobia to be also reflected in peer-reported homophobia. A significant genetic component, however, was self-report-specific (38%), suggesting that self-assessments alone produce inflated heritability estimates to some degree. Different explanations are discussed.

Decomposition of Variance for Spatial Cox Processes.

Science.gov (United States)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

2013-03-01

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.

Grammatical and lexical variance in English

CERN Document Server

Quirk, Randolph

2014-01-01

Written by one of Britain's most distinguished linguists, this book is concerned with the phenomenon of variance in English grammar and vocabulary across regional, social, stylistic and temporal space.

Variance decomposition in stochastic simulators.

Science.gov (United States)

Le Maître, O P; Knio, O M; Moraes, A

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Science.gov (United States)

Le Maître, O. P.; Knio, O. M.; Moraes, A.

2015-06-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance decomposition in stochastic simulators

Energy Technology Data Exchange (ETDEWEB)

Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

2015-06-28

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Variance-based Salt Body Reconstruction

KAUST Repository

Ovcharenko, Oleg

2017-05-26

Seismic inversions of salt bodies are challenging when updating velocity models based on Born approximation- inspired gradient methods. We propose a variance-based method for velocity model reconstruction in regions complicated by massive salt bodies. The novel idea lies in retrieving useful information from simultaneous updates corresponding to different single frequencies. Instead of the commonly used averaging of single-iteration monofrequency gradients, our algorithm iteratively reconstructs salt bodies in an outer loop based on updates from a set of multiple frequencies after a few iterations of full-waveform inversion. The variance among these updates is used to identify areas where considerable cycle-skipping occurs. In such areas, we update velocities by interpolating maximum velocities within a certain region. The result of several recursive interpolations is later used as a new starting model to improve results of conventional full-waveform inversion. An application on part of the BP 2004 model highlights the evolution of the proposed approach and demonstrates its effectiveness.

Variance decomposition in stochastic simulators

KAUST Repository

Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro

2015-01-01

This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

Minimum variance Monte Carlo importance sampling with parametric dependence

International Nuclear Information System (INIS)

Ragheb, M.M.H.; Halton, J.; Maynard, C.W.

1981-01-01

An approach for Monte Carlo Importance Sampling with parametric dependence is proposed. It depends upon obtaining by proper weighting over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adapted and other results rejected. Numerical calculation for the estimation of intergrals are compared to Crude Monte Carlo. Results explain the occurrences of the effective biases (even though the theoretical bias is zero) and infinite variances which arise in calculations involving severe biasing and a moderate number of historis. Extension to particle transport applications is briefly discussed. The approach constitutes an extension of a theory on the application of Monte Carlo for the calculation of functional dependences introduced by Frolov and Chentsov to biasing, or importance sample calculations; and is a generalization which avoids nonconvergence to the optimal values in some cases of a multistage method for variance reduction introduced by Spanier. (orig.) [de

Host nutrition alters the variance in parasite transmission potential.

Science.gov (United States)

Vale, Pedro F; Choisy, Marc; Little, Tom J

2013-04-23

The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts.

Age-dependent changes in mean and variance of gene expression across tissues in a twin cohort.

Science.gov (United States)

Viñuela, Ana; Brown, Andrew A; Buil, Alfonso; Tsai, Pei-Chien; Davies, Matthew N; Bell, Jordana T; Dermitzakis, Emmanouil T; Spector, Timothy D; Small, Kerrin S

2018-02-15

Changes in the mean and variance of gene expression with age have consequences for healthy aging and disease development. Age-dependent changes in phenotypic variance have been associated with a decline in regulatory functions leading to increase in disease risk. Here, we investigate age-related mean and variance changes in gene expression measured by RNA-seq of fat, skin, whole blood and derived lymphoblastoid cell lines (LCLs) expression from 855 adult female twins. We see evidence of up to 60% of age effects on transcription levels shared across tissues, and 47% of those on splicing. Using gene expression variance and discordance between genetically identical MZ twin pairs, we identify 137 genes with age-related changes in variance and 42 genes with age-related discordance between co-twins; implying the latter are driven by environmental effects. We identify four eQTLs whose effect on expression is age-dependent (FDR 5%). Combined, these results show a complicated mix of environmental and genetically driven changes in expression with age. Using the twin structure in our data, we show that additive genetic effects explain considerably more of the variance in gene expression than aging, but less that other environmental factors, potentially explaining why reliable expression-derived biomarkers for healthy-aging have proved elusive compared with those derived from methylation. © The Author(s) 2017. Published by Oxford University Press.

Exploring variance in residential electricity consumption: Household features and building properties

International Nuclear Information System (INIS)

Bartusch, Cajsa; Odlare, Monica; Wallin, Fredrik; Wester, Lars

2012-01-01

Highlights: ► Statistical analysis of variance are of considerable value in identifying key indicators for policy update. ► Variance in residential electricity use is partly explained by household features. ► Variance in residential electricity use is partly explained by building properties. ► Household behavior has a profound impact on individual electricity use. -- Abstract: Improved means of controlling electricity consumption plays an important part in boosting energy efficiency in the Swedish power market. Developing policy instruments to that end requires more in-depth statistics on electricity use in the residential sector, among other things. The aim of the study has accordingly been to assess the extent of variance in annual electricity consumption in single-family homes as well as to estimate the impact of household features and building properties in this respect using independent samples t-tests and one-way as well as univariate independent samples analyses of variance. Statistically significant variances associated with geographic area, heating system, number of family members, family composition, year of construction, electric water heater and electric underfloor heating have been established. The overall result of the analyses is nevertheless that variance in residential electricity consumption cannot be fully explained by independent variables related to household and building characteristics alone. As for the methodological approach, the results further suggest that methods for statistical analysis of variance are of considerable value in indentifying key indicators for policy update and development.

Capturing option anomalies with a variance-dependent pricing kernel

NARCIS (Netherlands)

Christoffersen, P.; Heston, S.; Jacobs, K.

2013-01-01

We develop a GARCH option model with a variance premium by combining the Heston-Nandi (2000) dynamic with a new pricing kernel that nests Rubinstein (1976) and Brennan (1979). While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is

29 CFR 1904.38 - Variances from the recordkeeping rule.

Science.gov (United States)

2010-07-01

..., DEPARTMENT OF LABOR RECORDING AND REPORTING OCCUPATIONAL INJURIES AND ILLNESSES Other OSHA Injury and Illness... he or she finds appropriate. (iv) If the Assistant Secretary grants your variance petition, OSHA will... Secretary is reviewing your variance petition. (4) If I have already been cited by OSHA for not following...

Meta-analysis of SNPs involved in variance heterogeneity using Levene's test for equal variances

Science.gov (United States)

Deng, Wei Q; Asma, Senay; Paré, Guillaume

2014-01-01

Meta-analysis is a commonly used approach to increase the sample size for genome-wide association searches when individual studies are otherwise underpowered. Here, we present a meta-analysis procedure to estimate the heterogeneity of the quantitative trait variance attributable to genetic variants using Levene's test without needing to exchange individual-level data. The meta-analysis of Levene's test offers the opportunity to combine the considerable sample size of a genome-wide meta-analysis to identify the genetic basis of phenotypic variability and to prioritize single-nucleotide polymorphisms (SNPs) for gene–gene and gene–environment interactions. The use of Levene's test has several advantages, including robustness to departure from the normality assumption, freedom from the influence of the main effects of SNPs, and no assumption of an additive genetic model. We conducted a meta-analysis of the log-transformed body mass index of 5892 individuals and identified a variant with a highly suggestive Levene's test P-value of 4.28E-06 near the NEGR1 locus known to be associated with extreme obesity. PMID:23921533

Analysis of ulnar variance as a risk factor for developing scaphoid nonunion.

Science.gov (United States)

Lirola-Palmero, S; Salvà-Coll, G; Terrades-Cladera, F J

2015-01-01

Ulnar variance may be a risk factor of developing scaphoid non-union. A review was made of the posteroanterior wrist radiographs of 95 patients who were diagnosed of scaphoid fracture. All fractures with displacement less than 1mm treated conservatively were included. The ulnar variance was measured in all patients. Ulnar variance was measured in standard posteroanterior wrist radiographs of 95 patients. Eighteen patients (19%) developed scaphoid nonunion, with a mean value of ulnar variance of -1.34 (-/+ 0.85) mm (CI -2.25 - 0.41). Seventy seven patients (81%) healed correctly, and the mean value of ulnar variance was -0.04 (-/+ 1.85) mm (CI -0.46 - 0.38). A significant difference was observed in the distribution of ulnar variance (pvariance less than -1mm, and ulnar variance greater than -1mm. It appears that patients with ulnar variance less than -1mm had an OR 4.58 (CI 1.51 to 13.89) with pvariance less than -1mm have a greater risk of developing scaphoid nonunion, OR 4.58 (CI 1.51 to 13.89) with p<.007. Copyright © 2014 SECOT. Published by Elsevier Espana. All rights reserved.

The dynamics of integrate-and-fire: mean versus variance modulations and dependence on baseline parameters.

Science.gov (United States)

Pressley, Joanna; Troyer, Todd W

2011-05-01

The leaky integrate-and-fire (LIF) is the simplest neuron model that captures the essential properties of neuronal signaling. Yet common intuitions are inadequate to explain basic properties of LIF responses to sinusoidal modulations of the input. Here we examine responses to low and moderate frequency modulations of both the mean and variance of the input current and quantify how these responses depend on baseline parameters. Across parameters, responses to modulations in the mean current are low pass, approaching zero in the limit of high frequencies. For very low baseline firing rates, the response cutoff frequency matches that expected from membrane integration. However, the cutoff shows a rapid, supralinear increase with firing rate, with a steeper increase in the case of lower noise. For modulations of the input variance, the gain at high frequency remains finite. Here, we show that the low-frequency responses depend strongly on baseline parameters and derive an analytic condition specifying the parameters at which responses switch from being dominated by low versus high frequencies. Additionally, we show that the resonant responses for variance modulations have properties not expected for common oscillatory resonances: they peak at frequencies higher than the baseline firing rate and persist when oscillatory spiking is disrupted by high noise. Finally, the responses to mean and variance modulations are shown to have a complementary dependence on baseline parameters at higher frequencies, resulting in responses to modulations of Poisson input rates that are independent of baseline input statistics.

Decomposition of variance in terms of conditional means

Directory of Open Access Journals (Sweden)

Alessandro Figà Talamanca

2013-05-01

Full Text Available Two different sets of data are used to test an apparently new approach to the analysis of the variance of a numerical variable which depends on qualitative variables. We suggest that this approach be used to complement other existing techniques to study the interdependence of the variables involved. According to our method, the variance is expressed as a sum of orthogonal components, obtained as differences of conditional means, with respect to the qualitative characters. The resulting expression for the variance depends on the ordering in which the characters are considered. We suggest an algorithm which leads to an ordering which is deemed natural. The first set of data concerns the score achieved by a population of students on an entrance examination based on a multiple choice test with 30 questions. In this case the qualitative characters are dyadic and correspond to correct or incorrect answer to each question. The second set of data concerns the delay to obtain the degree for a population of graduates of Italian universities. The variance in this case is analyzed with respect to a set of seven specific qualitative characters of the population studied (gender, previous education, working condition, parent's educational level, field of study, etc..

42 CFR 456.522 - Content of request for variance.

Science.gov (United States)

2010-10-01

... 42 Public Health 4 2010-10-01 2010-10-01 false Content of request for variance. 456.522 Section 456.522 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... perform UR within the time requirements for which the variance is requested and its good faith efforts to...

On the Endogeneity of the Mean-Variance Efficient Frontier.

Science.gov (United States)

Somerville, R. A.; O'Connell, Paul G. J.

2002-01-01

Explains that the endogeneity of the efficient frontier in the mean-variance model of portfolio selection is commonly obscured in portfolio selection literature and in widely used textbooks. Demonstrates endogeneity and discusses the impact of parameter changes on the mean-variance efficient frontier and on the beta coefficients of individual…

Variance and covariance calculations for nuclear materials accounting using ''MAVARIC''

International Nuclear Information System (INIS)

Nasseri, K.K.

1987-07-01

Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined

A versatile omnibus test for detecting mean and variance heterogeneity.

Science.gov (United States)

Cao, Ying; Wei, Peng; Bailey, Matthew; Kauwe, John S K; Maxwell, Taylor J

2014-01-01

Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (G × G), or gene-by-environment interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRT(MV)) or either effect alone (LRT(M) or LRT(V)) in the presence of covariates. Using extensive simulations for our method and others, we found that all parametric tests were sensitive to nonnormality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant, we demonstrate how LD can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D', and relatively low r² values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance-only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect G × G interactions and also how vQTL are related to relationship loci, and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait.

Variance and covariance calculations for nuclear materials accounting using 'MAVARIC'

International Nuclear Information System (INIS)

Nasseri, K.K.

1987-01-01

Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined

Global Variance Risk Premium and Forex Return Predictability

OpenAIRE

Aloosh, Arash

2014-01-01

In a long-run risk model with stochastic volatility and frictionless markets, I express expected forex returns as a function of consumption growth variances and stock variance risk premiums (VRPs)—the difference between the risk-neutral and statistical expectations of market return variation. This provides a motivation for using the forward-looking information available in stock market volatility indices to predict forex returns. Empirically, I find that stock VRPs predict forex returns at a ...

29 CFR 1920.2 - Variances.

Science.gov (United States)

2010-07-01

...) PROCEDURE FOR VARIATIONS FROM SAFETY AND HEALTH REGULATIONS UNDER THE LONGSHOREMEN'S AND HARBOR WORKERS...) or 6(d) of the Williams-Steiger Occupational Safety and Health Act of 1970 (29 U.S.C. 655). The... under the Williams-Steiger Occupational Safety and Health Act of 1970, and any variance from §§ 1910.13...

Zero-intelligence realized variance estimation

NARCIS (Netherlands)

Gatheral, J.; Oomen, R.C.A.

2010-01-01

Given a time series of intra-day tick-by-tick price data, how can realized variance be estimated? The obvious estimator—the sum of squared returns between trades—is biased by microstructure effects such as bid-ask bounce and so in the past, practitioners were advised to drop most of the data and

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

Science.gov (United States)

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this

The mean and variance of phylogenetic diversity under rarefaction.

Science.gov (United States)

Nipperess, David A; Matsen, Frederick A

2013-06-01

Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required.

Using variances to comply with resource conservation and recovery act treatment standards

International Nuclear Information System (INIS)

Ranek, N.L.

2002-01-01

When a waste generated, treated, or disposed of at a site in the United States is classified as hazardous under the Resource Conservation and Recovery Act and is destined for land disposal, the waste manager responsible for that site must select an approach to comply with land disposal restrictions (LDR) treatment standards. This paper focuses on the approach of obtaining a variance from existing, applicable LDR treatment standards. It describes the types of available variances, which include (1) determination of equivalent treatment (DET); (2) treatability variance; and (3) treatment variance for contaminated soil. The process for obtaining each type of variance is also described. Data are presented showing that historically the U.S. Environmental Protection Agency (EPA) processed DET petitions within one year of their date of submission. However, a 1999 EPA policy change added public participation to the DET petition review, which may lengthen processing time in the future. Regarding site-specific treatability variances, data are presented showing an EPA processing time of between 10 and 16 months. Only one generically applicable treatability variance has been granted, which took 30 months to process. No treatment variances for contaminated soil, which were added to the federal LDR program in 1998, are identified as having been granted.

Gini estimation under infinite variance

NARCIS (Netherlands)

A. Fontanari (Andrea); N.N. Taleb (Nassim Nicholas); P. Cirillo (Pasquale)

2018-01-01

textabstractWe study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index α∈(1,2)). We show that, in such a case, the Gini coefficient

Phenotypic variance explained by local ancestry in admixed African Americans.

Science.gov (United States)

Shriner, Daniel; Bentley, Amy R; Doumatey, Ayo P; Chen, Guanjie; Zhou, Jie; Adeyemo, Adebowale; Rotimi, Charles N

2015-01-01

We surveyed 26 quantitative traits and disease outcomes to understand the proportion of phenotypic variance explained by local ancestry in admixed African Americans. After inferring local ancestry as the number of African-ancestry chromosomes at hundreds of thousands of genotyped loci across all autosomes, we used a linear mixed effects model to estimate the variance explained by local ancestry in two large independent samples of unrelated African Americans. We found that local ancestry at major and polygenic effect genes can explain up to 20 and 8% of phenotypic variance, respectively. These findings provide evidence that most but not all additive genetic variance is explained by genetic markers undifferentiated by ancestry. These results also inform the proportion of health disparities due to genetic risk factors and the magnitude of error in association studies not controlling for local ancestry.

Continuous-Time Mean-Variance Portfolio Selection: A Stochastic LQ Framework

International Nuclear Information System (INIS)

Zhou, X.Y.; Li, D.

2000-01-01

This paper is concerned with a continuous-time mean-variance portfolio selection model that is formulated as a bicriteria optimization problem. The objective is to maximize the expected terminal return and minimize the variance of the terminal wealth. By putting weights on the two criteria one obtains a single objective stochastic control problem which is however not in the standard form due to the variance term involved. It is shown that this nonstandard problem can be 'embedded' into a class of auxiliary stochastic linear-quadratic (LQ) problems. The stochastic LQ control model proves to be an appropriate and effective framework to study the mean-variance problem in light of the recent development on general stochastic LQ problems with indefinite control weighting matrices. This gives rise to the efficient frontier in a closed form for the original portfolio selection problem

Replica approach to mean-variance portfolio optimization

Science.gov (United States)

Varga-Haszonits, Istvan; Caccioli, Fabio; Kondor, Imre

2016-12-01

We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the statistical physics of disordered systems. We find that the replica symmetry of the solution does not need to be assumed, but emerges as the unique solution of the optimization problem. We also check the stability of this solution and find that the eigenvalues of the Hessian are positive for r  =  N/T  optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.

The impact of wind generation on the electricity spot-market price level and variance: The Texas experience

International Nuclear Information System (INIS)

Woo, C.K.; Horowitz, I.; Moore, J.; Pacheco, A.

2011-01-01

The literature on renewable energy suggests that an increase in intermittent wind generation would reduce the spot electricity market price by displacing high fuel-cost marginal generation. Taking advantage of a large file of Texas-based 15-min data, we show that while rising wind generation does indeed tend to reduce the level of spot prices, it is also likely to enlarge the spot-price variance. The key policy implication is that increasing use of price risk management should accompany expanded deployment of wind generation. - Highlights: → Rising wind generation in ERCOT tends to reduce electricity spot prices. → Rising wind generation in ERCOT is also likely to enlarge the spot-price variance. → Increased price risk management should accompany expanded wind power deployment.

Realized Variance and Market Microstructure Noise

DEFF Research Database (Denmark)

Hansen, Peter R.; Lunde, Asger

2006-01-01

We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of market microstructure noise and that a simple kernel......-based estimator dominates the RV for the estimation of integrated variance (IV). An empirical analysis of the Dow Jones Industrial Average stocks reveals that market microstructure noise its time-dependent and correlated with increments in the efficient price. This has important implications for volatility...... estimation based on high-frequency data. Finally, we apply cointegration techniques to decompose transaction prices and bid-ask quotes into an estimate of the efficient price and noise. This framework enables us to study the dynamic effects on transaction prices and quotes caused by changes in the efficient...

Spot Variance Path Estimation and its Application to High Frequency Jump Testing

NARCIS (Netherlands)

Bos, C.S.; Janus, P.; Koopman, S.J.

2012-01-01

This paper considers spot variance path estimation from datasets of intraday high-frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects, and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used to

Raising the speed limit from 75 to 80mph on Utah rural interstates: Effects on vehicle speeds and speed variance.

Science.gov (United States)

Hu, Wen

2017-06-01

In November 2010 and October 2013, Utah increased speed limits on sections of rural interstates from 75 to 80mph. Effects on vehicle speeds and speed variance were examined. Speeds were measured in May 2010 and May 2014 within the new 80mph zones, and at a nearby spillover site and at more distant control sites where speed limits remained 75mph. Log-linear regression models estimated percentage changes in speed variance and mean speeds for passenger vehicles and large trucks associated with the speed limit increase. Logistic regression models estimated effects on the probability of passenger vehicles exceeding 80, 85, or 90mph and large trucks exceeding 80mph. Within the 80mph zones and at the spillover location in 2014, mean passenger vehicle speeds were significantly higher (4.1% and 3.5%, respectively), as were the probabilities that passenger vehicles exceeded 80mph (122.3% and 88.5%, respectively), than would have been expected without the speed limit increase. Probabilities that passenger vehicles exceeded 85 and 90mph were non-significantly higher than expected within the 80mph zones. For large trucks, the mean speed and probability of exceeding 80mph were higher than expected within the 80mph zones. Only the increase in mean speed was significant. Raising the speed limit was associated with non-significant increases in speed variance. The study adds to the wealth of evidence that increasing speed limits leads to higher travel speeds and an increased probability of exceeding the new speed limit. Results moreover contradict the claim that increasing speed limits reduces speed variance. Although the estimated increases in mean vehicle speeds may appear modest, prior research suggests such increases would be associated with substantial increases in fatal or injury crashes. This should be considered by lawmakers considering increasing speed limits. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

ANALISIS PORTOFOLIO RESAMPLED EFFICIENT FRONTIER BERDASARKAN OPTIMASI MEAN-VARIANCE

OpenAIRE

Abdurakhman, Abdurakhman

2008-01-01

Keputusan alokasi asset yang tepat pada investasi portofolio dapat memaksimalkan keuntungan dan atau meminimalkan risiko. Metode yang sering dipakai dalam optimasi portofolio adalah metode Mean-Variance Markowitz. Dalam prakteknya, metode ini mempunyai kelemahan tidak terlalu stabil. Sedikit perubahan dalam estimasi parameter input menyebabkan perubahan besar pada komposisi portofolio. Untuk itu dikembangkan metode optimasi portofolio yang dapat mengatasi ketidakstabilan metode Mean-Variance ...

Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time

OpenAIRE

Daheng Peng; Fang Zhang

2017-01-01

In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.

The asymptotic variance of departures in critically loaded queues

NARCIS (Netherlands)

Al Hanbali, Ahmad; Mandjes, M.R.H.; Nazarathy, Y.; Whitt, W.

2011-01-01

We consider the asymptotic variance of the departure counting process D(t) of the GI/G/1 queue; D(t) denotes the number of departures up to time t. We focus on the case where the system load ϱ equals 1, and prove that the asymptotic variance rate satisfies limt→∞varD(t) / t = λ(1 - 2 / π)(ca2 +

Coupled bias-variance tradeoff for cross-pose face recognition.

Science.gov (United States)

Li, Annan; Shan, Shiguang; Gao, Wen

2012-01-01

Subspace-based face representation can be looked as a regression problem. From this viewpoint, we first revisited the problem of recognizing faces across pose differences, which is a bottleneck in face recognition. Then, we propose a new approach for cross-pose face recognition using a regressor with a coupled bias-variance tradeoff. We found that striking a coupled balance between bias and variance in regression for different poses could improve the regressor-based cross-pose face representation, i.e., the regressor can be more stable against a pose difference. With the basic idea, ridge regression and lasso regression are explored. Experimental results on CMU PIE, the FERET, and the Multi-PIE face databases show that the proposed bias-variance tradeoff can achieve considerable reinforcement in recognition performance.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

Science.gov (United States)

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

Directory of Open Access Journals (Sweden)

Liyun Zhuang

2017-01-01

Full Text Available This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE, which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE. Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance.

Science.gov (United States)

Zhuang, Liyun; Guan, Yepeng

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image.

An elementary components of variance analysis for multi-center quality control

International Nuclear Information System (INIS)

Munson, P.J.; Rodbard, D.

1977-01-01

The serious variability of RIA results from different laboratories indicates the need for multi-laboratory collaborative quality control (QC) studies. Statistical analysis methods for such studies using an 'analysis of variance with components of variance estimation' are discussed. This technique allocates the total variance into components corresponding to between-laboratory, between-assay, and residual or within-assay variability. Components of variance analysis also provides an intelligent way to combine the results of several QC samples run at different evels, from which we may decide if any component varies systematically with dose level; if not, pooling of estimates becomes possible. We consider several possible relationships of standard deviation to the laboratory mean. Each relationship corresponds to an underlying statistical model, and an appropriate analysis technique. Tests for homogeneity of variance may be used to determine if an appropriate model has been chosen, although the exact functional relationship of standard deviation to lab mean may be difficult to establish. Appropriate graphical display of the data aids in visual understanding of the data. A plot of the ranked standard deviation vs. ranked laboratory mean is a convenient way to summarize a QC study. This plot also allows determination of the rank correlation, which indicates a net relationship of variance to laboratory mean. (orig.) [de

Explicit formulas for the variance of discounted life-cycle cost

International Nuclear Information System (INIS)

Noortwijk, Jan M. van

2003-01-01

In life-cycle costing analyses, optimal design is usually achieved by minimising the expected value of the discounted costs. As well as the expected value, the corresponding variance may be useful for estimating, for example, the uncertainty bounds of the calculated discounted costs. However, general explicit formulas for calculating the variance of the discounted costs over an unbounded time horizon are not yet available. In this paper, explicit formulas for this variance are presented. They can be easily implemented in software to optimise structural design and maintenance management. The use of the mathematical results is illustrated with some examples

Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time

Directory of Open Access Journals (Sweden)

Daheng Peng

2017-10-01

Full Text Available In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.

Non-destructive X-ray Computed Tomography (XCT) Analysis of Sediment Variance in Marine Cores

Science.gov (United States)

Oti, E.; Polyak, L. V.; Dipre, G.; Sawyer, D.; Cook, A.

2015-12-01

Benthic activity within marine sediments can alter the physical properties of the sediment as well as indicate nutrient flux and ocean temperatures. We examine burrowing features in sediment cores from the western Arctic Ocean collected during the 2005 Healy-Oden TransArctic Expedition (HOTRAX) and from the Gulf of Mexico Integrated Ocean Drilling Program (IODP) Expedition 308. While traditional methods for studying bioturbation require physical dissection of the cores, we assess burrowing using an X-ray computed tomography (XCT) scanner. XCT noninvasively images the sediment cores in three dimensions and produces density sensitive images suitable for quantitative analysis. XCT units are recorded as Hounsfield Units (HU), where -999 is air, 0 is water, and 4000-5000 would be a higher density mineral, such as pyrite. We rely on the fundamental assumption that sediments are deposited horizontally, and we analyze the variance over each flat-lying slice. The variance describes the spread of pixel values over a slice. When sediments are reworked, drawing higher and lower density matrix into a layer, the variance increases. Examples of this can be seen in two slices in core 19H-3A from Site U1324 of IODP Expedition 308. The first slice, located 165.6 meters below sea floor consists of relatively undisturbed sediment. Because of this, the majority of the sediment values fall between 1406 and 1497 HU, thus giving the slice a comparatively small variance of 819.7. The second slice, located 166.1 meters below sea floor, features a lower density sediment matrix disturbed by burrow tubes and the inclusion of a high density mineral. As a result, the Hounsfield Units have a larger variance of 1,197.5, which is a result of sediment matrix values that range from 1220 to 1260 HU, the high-density mineral value of 1920 HU and the burrow tubes that range from 1300 to 1410 HU. Analyzing this variance allows us to observe changes in the sediment matrix and more specifically capture

An elementary components of variance analysis for multi-centre quality control

International Nuclear Information System (INIS)

Munson, P.J.; Rodbard, D.

1978-01-01

The serious variability of RIA results from different laboratories indicates the need for multi-laboratory collaborative quality-control (QC) studies. Simple graphical display of data in the form of histograms is useful but insufficient. The paper discusses statistical analysis methods for such studies using an ''analysis of variance with components of variance estimation''. This technique allocates the total variance into components corresponding to between-laboratory, between-assay, and residual or within-assay variability. Problems with RIA data, e.g. severe non-uniformity of variance and/or departure from a normal distribution violate some of the usual assumptions underlying analysis of variance. In order to correct these problems, it is often necessary to transform the data before analysis by using a logarithmic, square-root, percentile, ranking, RIDIT, ''Studentizing'' or other transformation. Ametric transformations such as ranks or percentiles protect against the undue influence of outlying observations, but discard much intrinsic information. Several possible relationships of standard deviation to the laboratory mean are considered. Each relationship corresponds to an underlying statistical model and an appropriate analysis technique. Tests for homogeneity of variance may be used to determine whether an appropriate model has been chosen, although the exact functional relationship of standard deviation to laboratory mean may be difficult to establish. Appropriate graphical display aids visual understanding of the data. A plot of the ranked standard deviation versus ranked laboratory mean is a convenient way to summarize a QC study. This plot also allows determination of the rank correlation, which indicates a net relationship of variance to laboratory mean

Using variance structure to quantify responses to perturbation in fish catches

Science.gov (United States)

Vidal, Tiffany E.; Irwin, Brian J.; Wagner, Tyler; Rudstam, Lars G.; Jackson, James R.; Bence, James R.

2017-01-01

We present a case study evaluation of gill-net catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including the disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gill-net time series and a negative binomial linear mixed model to partition the variability in catches into spatial and coherent temporal variance components, hypothesizing that variance partitioning can help quantify spatiotemporal variability and determine whether variance structure differs before and after large-scale perturbations. We found that the mean catch and the total variability of catches decreased following perturbation but that not all sampling locations responded in a consistent manner. There was also evidence of some spatial homogenization concurrent with a restructuring of the relative productivity of individual sites. Specifically, offshore sites generally became more productive following the estimated break point in the gill-net time series. These results provide support for the idea that variance structure is responsive to large-scale perturbations; therefore, variance components have potential utility as statistical indicators of response to a changing environment more broadly. The modeling approach described herein is flexible and would be transferable to other systems and metrics. For example, variance partitioning could be used to examine responses to alternative management regimes, to compare variability across physiographic regions, and to describe differences among climate zones. Understanding how individual variance components respond to perturbation may yield finer-scale insights into ecological shifts than focusing on patterns in the mean responses or total variability alone.

A mean–variance objective for robust production optimization in uncertain geological scenarios

DEFF Research Database (Denmark)

Capolei, Andrea; Suwartadi, Eka; Foss, Bjarne

2014-01-01

directly. In the mean–variance bi-criterion objective function risk appears directly, it also considers an ensemble of reservoir models, and has robust optimization as a special extreme case. The mean–variance objective is common for portfolio optimization problems in finance. The Markowitz portfolio...... optimization problem is the original and simplest example of a mean–variance criterion for mitigating risk. Risk is mitigated in oil production by including both the expected NPV (mean of NPV) and the risk (variance of NPV) for the ensemble of possible reservoir models. With the inclusion of the risk...

ACCOUNTING FOR COSMIC VARIANCE IN STUDIES OF GRAVITATIONALLY LENSED HIGH-REDSHIFT GALAXIES IN THE HUBBLE FRONTIER FIELD CLUSTERS

Energy Technology Data Exchange (ETDEWEB)

Robertson, Brant E.; Stark, Dan P. [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States); Ellis, Richard S. [Department of Astronomy, California Institute of Technology, MS 249-17, Pasadena, CA 91125 (United States); Dunlop, James S.; McLure, Ross J.; McLeod, Derek, E-mail: brant@email.arizona.edu [Institute for Astronomy, University of Edinburgh, Royal Observatory, Edinburgh EH9 3HJ (United Kingdom)

2014-12-01

Strong gravitational lensing provides a powerful means for studying faint galaxies in the distant universe. By magnifying the apparent brightness of background sources, massive clusters enable the detection of galaxies fainter than the usual sensitivity limit for blank fields. However, this gain in effective sensitivity comes at the cost of a reduced survey volume and, in this Letter, we demonstrate that there is an associated increase in the cosmic variance uncertainty. As an example, we show that the cosmic variance uncertainty of the high-redshift population viewed through the Hubble Space Telescope Frontier Field cluster Abell 2744 increases from ∼35% at redshift z ∼ 7 to ≳ 65% at z ∼ 10. Previous studies of high-redshift galaxies identified in the Frontier Fields have underestimated the cosmic variance uncertainty that will affect the ultimate constraints on both the faint-end slope of the high-redshift luminosity function and the cosmic star formation rate density, key goals of the Frontier Field program.

ACCOUNTING FOR COSMIC VARIANCE IN STUDIES OF GRAVITATIONALLY LENSED HIGH-REDSHIFT GALAXIES IN THE HUBBLE FRONTIER FIELD CLUSTERS

International Nuclear Information System (INIS)

Robertson, Brant E.; Stark, Dan P.; Ellis, Richard S.; Dunlop, James S.; McLure, Ross J.; McLeod, Derek

2014-01-01

Strong gravitational lensing provides a powerful means for studying faint galaxies in the distant universe. By magnifying the apparent brightness of background sources, massive clusters enable the detection of galaxies fainter than the usual sensitivity limit for blank fields. However, this gain in effective sensitivity comes at the cost of a reduced survey volume and, in this Letter, we demonstrate that there is an associated increase in the cosmic variance uncertainty. As an example, we show that the cosmic variance uncertainty of the high-redshift population viewed through the Hubble Space Telescope Frontier Field cluster Abell 2744 increases from ∼35% at redshift z ∼ 7 to ≳ 65% at z ∼ 10. Previous studies of high-redshift galaxies identified in the Frontier Fields have underestimated the cosmic variance uncertainty that will affect the ultimate constraints on both the faint-end slope of the high-redshift luminosity function and the cosmic star formation rate density, key goals of the Frontier Field program

Accounting for Cosmic Variance in Studies of Gravitationally Lensed High-redshift Galaxies in the Hubble Frontier Field Clusters

Science.gov (United States)

Robertson, Brant E.; Ellis, Richard S.; Dunlop, James S.; McLure, Ross J.; Stark, Dan P.; McLeod, Derek

2014-12-01

Strong gravitational lensing provides a powerful means for studying faint galaxies in the distant universe. By magnifying the apparent brightness of background sources, massive clusters enable the detection of galaxies fainter than the usual sensitivity limit for blank fields. However, this gain in effective sensitivity comes at the cost of a reduced survey volume and, in this Letter, we demonstrate that there is an associated increase in the cosmic variance uncertainty. As an example, we show that the cosmic variance uncertainty of the high-redshift population viewed through the Hubble Space Telescope Frontier Field cluster Abell 2744 increases from ~35% at redshift z ~ 7 to >~ 65% at z ~ 10. Previous studies of high-redshift galaxies identified in the Frontier Fields have underestimated the cosmic variance uncertainty that will affect the ultimate constraints on both the faint-end slope of the high-redshift luminosity function and the cosmic star formation rate density, key goals of the Frontier Field program.

Marangoni instability in a thin film heated from below: Effect of nonmonotonic dependence of surface tension on temperature

Science.gov (United States)

Sarma, Rajkumar; Mondal, Pranab Kumar

2018-04-01

We investigate Marangoni instability in a thin liquid film resting on a substrate of low thermal conductivity and separated from the surrounding gas phase by a deformable free surface. Considering a nonmonotonic variation of surface tension with temperature, here we analytically derive the neutral stability curve for the monotonic and oscillatory modes of instability (for both the long-wave and short-wave perturbations) under the framework of linear stability analysis. For the long-wave instability, we derive a set of amplitude equations using the scaling k ˜(Bi) 1 /2 , where k is the wave number and Bi is the Biot number. Through this investigation, we demonstrate that for such a fluid layer upon heating from below, both monotonic and oscillatory instability can appear for a certain range of the dimensionless parameters, viz., Biot number (Bi ) , Galileo number (Ga ) , and inverse capillary number (Σ ) . Moreover, we unveil, through this study, the influential role of the above-mentioned parameters on the stability of the system and identify the critical values of these parameters above which instability initiates in the liquid layer.

Asymptotic variance of grey-scale surface area estimators

DEFF Research Database (Denmark)

Svane, Anne Marie

Grey-scale local algorithms have been suggested as a fast way of estimating surface area from grey-scale digital images. Their asymptotic mean has already been described. In this paper, the asymptotic behaviour of the variance is studied in isotropic and sufficiently smooth settings, resulting...... in a general asymptotic bound. For compact convex sets with nowhere vanishing Gaussian curvature, the asymptotics can be described more explicitly. As in the case of volume estimators, the variance is decomposed into a lattice sum and an oscillating term of at most the same magnitude....

Prediction-error variance in Bayesian model updating: a comparative study

Science.gov (United States)

Asadollahi, Parisa; Li, Jian; Huang, Yong

2017-04-01

In Bayesian model updating, the likelihood function is commonly formulated by stochastic embedding in which the maximum information entropy probability model of prediction error variances plays an important role and it is Gaussian distribution subject to the first two moments as constraints. The selection of prediction error variances can be formulated as a model class selection problem, which automatically involves a trade-off between the average data-fit of the model class and the information it extracts from the data. Therefore, it is critical for the robustness in the updating of the structural model especially in the presence of modeling errors. To date, three ways of considering prediction error variances have been seem in the literature: 1) setting constant values empirically, 2) estimating them based on the goodness-of-fit of the measured data, and 3) updating them as uncertain parameters by applying Bayes' Theorem at the model class level. In this paper, the effect of different strategies to deal with the prediction error variances on the model updating performance is investigated explicitly. A six-story shear building model with six uncertain stiffness parameters is employed as an illustrative example. Transitional Markov Chain Monte Carlo is used to draw samples of the posterior probability density function of the structure model parameters as well as the uncertain prediction variances. The different levels of modeling uncertainty and complexity are modeled through three FE models, including a true model, a model with more complexity, and a model with modeling error. Bayesian updating is performed for the three FE models considering the three aforementioned treatments of the prediction error variances. The effect of number of measurements on the model updating performance is also examined in the study. The results are compared based on model class assessment and indicate that updating the prediction error variances as uncertain parameters at the model

A random variance model for detection of differential gene expression in small microarray experiments.

Science.gov (United States)

Wright, George W; Simon, Richard M

2003-12-12

Microarray techniques provide a valuable way of characterizing the molecular nature of disease. Unfortunately expense and limited specimen availability often lead to studies with small sample sizes. This makes accurate estimation of variability difficult, since variance estimates made on a gene by gene basis will have few degrees of freedom, and the assumption that all genes share equal variance is unlikely to be true. We propose a model by which the within gene variances are drawn from an inverse gamma distribution, whose parameters are estimated across all genes. This results in a test statistic that is a minor variation of those used in standard linear models. We demonstrate that the model assumptions are valid on experimental data, and that the model has more power than standard tests to pick up large changes in expression, while not increasing the rate of false positives. This method is incorporated into BRB-ArrayTools version 3.0 (http://linus.nci.nih.gov/BRB-ArrayTools.html). ftp://linus.nci.nih.gov/pub/techreport/RVM_supplement.pdf

A characterization of optimal portfolios under the tail mean-variance criterion

OpenAIRE

Owadally, I.; Landsman, Z.

2013-01-01

The tail mean–variance model was recently introduced for use in risk management and portfolio choice; it involves a criterion that focuses on the risk of rare but large losses, which is particularly important when losses have heavy-tailed distributions. If returns or losses follow a multivariate elliptical distribution, the use of risk measures that satisfy certain well-known properties is equivalent to risk management in the classical mean–variance framework. The tail mean–variance criterion...

Gender variance in childhood and sexual orientation in adulthood: a prospective study.

Science.gov (United States)

Steensma, Thomas D; van der Ende, Jan; Verhulst, Frank C; Cohen-Kettenis, Peggy T

2013-11-01

Several retrospective and prospective studies have reported on the association between childhood gender variance and sexual orientation and gender discomfort in adulthood. In most of the retrospective studies, samples were drawn from the general population. The samples in the prospective studies consisted of clinically referred children. In understanding the extent to which the association applies for the general population, prospective studies using random samples are needed. This prospective study examined the association between childhood gender variance, and sexual orientation and gender discomfort in adulthood in the general population. In 1983, we measured childhood gender variance, in 406 boys and 473 girls. In 2007, sexual orientation and gender discomfort were assessed. Childhood gender variance was measured with two items from the Child Behavior Checklist/4-18. Sexual orientation was measured for four parameters of sexual orientation (attraction, fantasy, behavior, and identity). Gender discomfort was assessed by four questions (unhappiness and/or uncertainty about one's gender, wish or desire to be of the other gender, and consideration of living in the role of the other gender). For both men and women, the presence of childhood gender variance was associated with homosexuality for all four parameters of sexual orientation, but not with bisexuality. The report of adulthood homosexuality was 8 to 15 times higher for participants with a history of gender variance (10.2% to 12.2%), compared to participants without a history of gender variance (1.2% to 1.7%). The presence of childhood gender variance was not significantly associated with gender discomfort in adulthood. This study clearly showed a significant association between childhood gender variance and a homosexual sexual orientation in adulthood in the general population. In contrast to the findings in clinically referred gender-variant children, the presence of a homosexual sexual orientation in

29 CFR 1926.2 - Variances from safety and health standards.

Science.gov (United States)

2010-07-01

... from safety and health standards. (a) Variances from standards which are, or may be, published in this... 29 Labor 8 2010-07-01 2010-07-01 false Variances from safety and health standards. 1926.2 Section 1926.2 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION...

Temperature variance study in Monte-Carlo photon transport theory

International Nuclear Information System (INIS)

Giorla, J.

1985-10-01

We study different Monte-Carlo methods for solving radiative transfer problems, and particularly Fleck's Monte-Carlo method. We first give the different time-discretization schemes and the corresponding stability criteria. Then we write the temperature variance as a function of the variances of temperature and absorbed energy at the previous time step. Finally we obtain some stability criteria for the Monte-Carlo method in the stationary case [fr

Study of the variance of a Monte Carlo calculation. Application to weighting; Etude de la variance d'un calcul de Monte Carlo. Application a la ponderation

Energy Technology Data Exchange (ETDEWEB)

Lanore, Jeanne-Marie [Commissariat a l' Energie Atomique - CEA, Centre d' Etudes Nucleaires de Fontenay-aux-Roses, Direction des Piles Atomiques, Departement des Etudes de Piles, Service d' Etudes de Protections de Piles (France)

1969-04-15

One of the main difficulties in Monte Carlo computations is the estimation of the results variance. Generally, only an apparent variance can be observed over a few calculations, often very different from the actual variance. By studying a large number of short calculations, the authors have tried to evaluate the real variance, and then to apply the obtained results to the optimization of the computations. The program used is the Poker one-dimensional Monte Carlo program. Calculations are performed in two types of fictitious environments: a body with constant cross section, without absorption, where all shocks are elastic and isotropic; a body with variable cross section (presenting a very pronounced peak and hole), with an anisotropy for high energy elastic shocks, and with the possibility of inelastic shocks (this body presents all the features that can appear in a real case)

Adjustment of heterogenous variances and a calving year effect in ...

African Journals Online (AJOL)

Data at the beginning and at the end of lactation period, have higher variances than tests in the middle of the lactation. Furthermore, first lactations have lower mean and variances compared to second and third lactations. This is a deviation from the basic assumptions required for the application of repeatability models.

Estimating Predictive Variance for Statistical Gas Distribution Modelling

International Nuclear Information System (INIS)

Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo

2009-01-01

Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.

The derivative based variance sensitivity analysis for the distribution parameters and its computation

International Nuclear Information System (INIS)

Wang, Pan; Lu, Zhenzhou; Ren, Bo; Cheng, Lei

2013-01-01

The output variance is an important measure for the performance of a structural system, and it is always influenced by the distribution parameters of inputs. In order to identify the influential distribution parameters and make it clear that how those distribution parameters influence the output variance, this work presents the derivative based variance sensitivity decomposition according to Sobol′s variance decomposition, and proposes the derivative based main and total sensitivity indices. By transforming the derivatives of various orders variance contributions into the form of expectation via kernel function, the proposed main and total sensitivity indices can be seen as the “by-product” of Sobol′s variance based sensitivity analysis without any additional output evaluation. Since Sobol′s variance based sensitivity indices have been computed efficiently by the sparse grid integration method, this work also employs the sparse grid integration method to compute the derivative based main and total sensitivity indices. Several examples are used to demonstrate the rationality of the proposed sensitivity indices and the accuracy of the applied method

A Mean-Variance Criterion for Economic Model Predictive Control of Stochastic Linear Systems

DEFF Research Database (Denmark)

Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik

2014-01-01

, the tractability of the resulting optimal control problem is addressed. We use a power management case study to compare different variations of the mean-variance strategy with EMPC based on the certainty equivalence principle. The certainty equivalence strategy is much more computationally efficient than the mean......-variance strategies, but it does not account for the variance of the uncertain parameters. Openloop simulations suggest that a single-stage mean-variance approach yields a significantly lower operating cost than the certainty equivalence strategy. In closed-loop, the single-stage formulation is overly conservative...... be modified to perform almost as well as the two-stage mean-variance formulation. Nevertheless, we argue that the mean-variance approach can be used both as a strategy for evaluating less computational demanding methods such as the certainty equivalence method, and as an individual control strategy when...

Investigating the minimum achievable variance in a Monte Carlo criticality calculation

Energy Technology Data Exchange (ETDEWEB)

Christoforou, Stavros; Eduard Hoogenboom, J. [Delft University of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)

2008-07-01

The sources of variance in a Monte Carlo criticality calculation are identified and their contributions analyzed. A zero-variance configuration is initially simulated using analytically calculated adjoint functions for biasing. From there, the various sources are analyzed. It is shown that the minimum threshold comes from the fact that the fission source is approximated. In addition, the merits of a simple variance reduction method, such as implicit capture, are shown when compared to an analog simulation. Finally, it is shown that when non-exact adjoint functions are used for biasing, the variance reduction is rather insensitive to the quality of the adjoints, suggesting that the generation of the adjoints should have as low CPU cost as possible, in order to o et the CPU cost in the implementation of the biasing of a simulation. (authors)

Automatic Bayes Factors for Testing Equality- and Inequality-Constrained Hypotheses on Variances.

Science.gov (United States)

Böing-Messing, Florian; Mulder, Joris

2018-05-03

In comparing characteristics of independent populations, researchers frequently expect a certain structure of the population variances. These expectations can be formulated as hypotheses with equality and/or inequality constraints on the variances. In this article, we consider the Bayes factor for testing such (in)equality-constrained hypotheses on variances. Application of Bayes factors requires specification of a prior under every hypothesis to be tested. However, specifying subjective priors for variances based on prior information is a difficult task. We therefore consider so-called automatic or default Bayes factors. These methods avoid the need for the user to specify priors by using information from the sample data. We present three automatic Bayes factors for testing variances. The first is a Bayes factor with equal priors on all variances, where the priors are specified automatically using a small share of the information in the sample data. The second is the fractional Bayes factor, where a fraction of the likelihood is used for automatic prior specification. The third is an adjustment of the fractional Bayes factor such that the parsimony of inequality-constrained hypotheses is properly taken into account. The Bayes factors are evaluated by investigating different properties such as information consistency and large sample consistency. Based on this evaluation, it is concluded that the adjusted fractional Bayes factor is generally recommendable for testing equality- and inequality-constrained hypotheses on variances.

UV spectral fingerprinting and analysis of variance-principal component analysis: a useful tool for characterizing sources of variance in plant materials.

Science.gov (United States)

Luthria, Devanand L; Mukhopadhyay, Sudarsan; Robbins, Rebecca J; Finley, John W; Banuelos, Gary S; Harnly, James M

2008-07-23

UV spectral fingerprints, in combination with analysis of variance-principal components analysis (ANOVA-PCA), can differentiate between cultivars and growing conditions (or treatments) and can be used to identify sources of variance. Broccoli samples, composed of two cultivars, were grown under seven different conditions or treatments (four levels of Se-enriched irrigation waters, organic farming, and conventional farming with 100 and 80% irrigation based on crop evaporation and transpiration rate). Freeze-dried powdered samples were extracted with methanol-water (60:40, v/v) and analyzed with no prior separation. Spectral fingerprints were acquired for the UV region (220-380 nm) using a 50-fold dilution of the extract. ANOVA-PCA was used to construct subset matrices that permitted easy verification of the hypothesis that cultivar and treatment contributed to a difference in the chemical expression of the broccoli. The sums of the squares of the same matrices were used to show that cultivar, treatment, and analytical repeatability contributed 30.5, 68.3, and 1.2% of the variance, respectively.

Levine's guide to SPSS for analysis of variance

CERN Document Server

Braver, Sanford L; Page, Melanie

2003-01-01

A greatly expanded and heavily revised second edition, this popular guide provides instructions and clear examples for running analyses of variance (ANOVA) and several other related statistical tests of significance with SPSS. No other guide offers the program statements required for the more advanced tests in analysis of variance. All of the programs in the book can be run using any version of SPSS, including versions 11 and 11.5. A table at the end of the preface indicates where each type of analysis (e.g., simple comparisons) can be found for each type of design (e.g., mixed two-factor desi

A load factor based mean-variance analysis for fuel diversification

Energy Technology Data Exchange (ETDEWEB)

Gotham, Douglas; Preckel, Paul; Ruangpattana, Suriya [State Utility Forecasting Group, Purdue University, West Lafayette, IN (United States); Muthuraman, Kumar [McCombs School of Business, University of Texas, Austin, TX (United States); Rardin, Ronald [Department of Industrial Engineering, University of Arkansas, Fayetteville, AR (United States)

2009-03-15

Fuel diversification implies the selection of a mix of generation technologies for long-term electricity generation. The goal is to strike a good balance between reduced costs and reduced risk. The method of analysis that has been advocated and adopted for such studies is the mean-variance portfolio analysis pioneered by Markowitz (Markowitz, H., 1952. Portfolio selection. Journal of Finance 7(1) 77-91). However the standard mean-variance methodology, does not account for the ability of various fuels/technologies to adapt to varying loads. Such analysis often provides results that are easily dismissed by regulators and practitioners as unacceptable, since load cycles play critical roles in fuel selection. To account for such issues and still retain the convenience and elegance of the mean-variance approach, we propose a variant of the mean-variance analysis using the decomposition of the load into various types and utilizing the load factors of each load type. We also illustrate the approach using data for the state of Indiana and demonstrate the ability of the model in providing useful insights. (author)

Mixed emotions: Sensitivity to facial variance in a crowd of faces.

Science.gov (United States)

Haberman, Jason; Lee, Pegan; Whitney, David

2015-01-01

The visual system automatically represents summary information from crowds of faces, such as the average expression. This is a useful heuristic insofar as it provides critical information about the state of the world, not simply information about the state of one individual. However, the average alone is not sufficient for making decisions about how to respond to a crowd. The variance or heterogeneity of the crowd--the mixture of emotions--conveys information about the reliability of the average, essential for determining whether the average can be trusted. Despite its importance, the representation of variance within a crowd of faces has yet to be examined. This is addressed here in three experiments. In the first experiment, observers viewed a sample set of faces that varied in emotion, and then adjusted a subsequent set to match the variance of the sample set. To isolate variance as the summary statistic of interest, the average emotion of both sets was random. Results suggested that observers had information regarding crowd variance. The second experiment verified that this was indeed a uniquely high-level phenomenon, as observers were unable to derive the variance of an inverted set of faces as precisely as an upright set of faces. The third experiment replicated and extended the first two experiments using method-of-constant-stimuli. Together, these results show that the visual system is sensitive to emergent information about the emotional heterogeneity, or ambivalence, in crowds of faces.

Variance Swap Replication: Discrete or Continuous?

Directory of Open Access Journals (Sweden)

Fabien Le Floc’h

2018-02-01

Full Text Available The popular replication formula to price variance swaps assumes continuity of traded option strikes. In practice, however, there is only a discrete set of option strikes traded on the market. We present here different discrete replication strategies and explain why the continuous replication price is more relevant.

Impact of Damping Uncertainty on SEA Model Response Variance

Science.gov (United States)

Schiller, Noah; Cabell, Randolph; Grosveld, Ferdinand

2010-01-01

Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

The Impact of Jump Distributions on the Implied Volatility of Variance

DEFF Research Database (Denmark)

Nicolato, Elisa; Pisani, Camilla; Pedersen, David Sloth

2017-01-01

We consider a tractable affine stochastic volatility model that generalizes the seminal Heston (1993) model by augmenting it with jumps in the instantaneous variance process. In this framework, we consider both realized variance options and VIX options, and we examine the impact of the distribution...... of jumps on the associated implied volatility smile. We provide sufficient conditions for the asymptotic behavior of the implied volatility of variance for small and large strikes. In particular, by selecting alternative jump distributions, we show that one can obtain fundamentally different shapes...

Replication Variance Estimation under Two-phase Sampling in the Presence of Non-response

Directory of Open Access Journals (Sweden)

Muqaddas Javed

2014-09-01

Full Text Available Kim and Yu (2011 discussed replication variance estimator for two-phase stratified sampling. In this paper estimators for mean have been proposed in two-phase stratified sampling for different situation of existence of non-response at first phase and second phase. The expressions of variances of these estimators have been derived. Furthermore, replication-based jackknife variance estimators of these variances have also been derived. Simulation study has been conducted to investigate the performance of the suggested estimators.

How the Weak Variance of Momentum Can Turn Out to be Negative

Science.gov (United States)

Feyereisen, M. R.

2015-05-01

Weak values are average quantities, therefore investigating their associated variance is crucial in understanding their place in quantum mechanics. We develop the concept of a position-postselected weak variance of momentum as cohesively as possible, building primarily on material from Moyal (Mathematical Proceedings of the Cambridge Philosophical Society, Cambridge University Press, Cambridge, 1949) and Sonego (Found Phys 21(10):1135, 1991) . The weak variance is defined in terms of the Wigner function, using a standard construction from probability theory. We show this corresponds to a measurable quantity, which is not itself a weak value. It also leads naturally to a connection between the imaginary part of the weak value of momentum and the quantum potential. We study how the negativity of the Wigner function causes negative weak variances, and the implications this has on a class of `subquantum' theories. We also discuss the role of weak variances in studying determinism, deriving the classical limit from a variational principle.

Variance gradients and uncertainty budgets for nonlinear measurement functions with independent inputs

International Nuclear Information System (INIS)

Campanelli, Mark; Kacker, Raghu; Kessel, Rüdiger

2013-01-01

A novel variance-based measure for global sensitivity analysis, termed a variance gradient (VG), is presented for constructing uncertainty budgets under the Guide to the Expression of Uncertainty in Measurement (GUM) framework for nonlinear measurement functions with independent inputs. The motivation behind VGs is the desire of metrologists to understand which inputs' variance reductions would most effectively reduce the variance of the measurand. VGs are particularly useful when the application of the first supplement to the GUM is indicated because of the inadequacy of measurement function linearization. However, VGs reduce to a commonly understood variance decomposition in the case of a linear(ized) measurement function with independent inputs for which the original GUM readily applies. The usefulness of VGs is illustrated by application to an example from the first supplement to the GUM, as well as to the benchmark Ishigami function. A comparison of VGs to other available sensitivity measures is made. (paper)

Variance in parametric images: direct estimation from parametric projections

International Nuclear Information System (INIS)

Maguire, R.P.; Leenders, K.L.; Spyrou, N.M.

2000-01-01

Recent work has shown that it is possible to apply linear kinetic models to dynamic projection data in PET in order to calculate parameter projections. These can subsequently be back-projected to form parametric images - maps of parameters of physiological interest. Critical to the application of these maps, to test for significant changes between normal and pathophysiology, is an assessment of the statistical uncertainty. In this context, parametric images also include simple integral images from, e.g., [O-15]-water used to calculate statistical parametric maps (SPMs). This paper revisits the concept of parameter projections and presents a more general formulation of the parameter projection derivation as well as a method to estimate parameter variance in projection space, showing which analysis methods (models) can be used. Using simulated pharmacokinetic image data we show that a method based on an analysis in projection space inherently calculates the mathematically rigorous pixel variance. This results in an estimation which is as accurate as either estimating variance in image space during model fitting, or estimation by comparison across sets of parametric images - as might be done between individuals in a group pharmacokinetic PET study. The method based on projections has, however, a higher computational efficiency, and is also shown to be more precise, as reflected in smooth variance distribution images when compared to the other methods. (author)

A geometric approach to multiperiod mean variance optimization of assets and liabilities

OpenAIRE

Leippold, Markus; Trojani, Fabio; Vanini, Paolo

2005-01-01

We present a geometric approach to discrete time multiperiod mean variance portfolio optimization that largely simplifies the mathematical analysis and the economic interpretation of such model settings. We show that multiperiod mean variance optimal policies can be decomposed in an orthogonal set of basis strategies, each having a clear economic interpretation. This implies that the corresponding multi period mean variance frontiers are spanned by an orthogonal basis of dynamic returns. Spec...

Nonmonotonous changes of thymus nuclei lipid metabolism upon chronic gamma-radiation of rats at a dose-rate of 3 c Gy/Day

International Nuclear Information System (INIS)

Kulagina, T.P.; Kolomijtseva, I.K.; Moiseeva, S.A.; Kuzin, A.M.

2000-01-01

The dynamics of changes in the thymus nuclei lipid metabolism under chronic gamma-radiation in low doses with the dose rate of 3 cGy/day is studied. It is shown, that at the 25 cGy dose rate there takes place activation of exchange in the fatly-acid part of the phospholipid molecule with simultaneous activation of the cholesterol and fatty acids synthesis. The synthesis of cholesterol and fatty acids at 50 cGy remains activated, whereas metabolism of the fatty-acid part of the phospholipids molecule is sharply depressed. The identified changes reveal the similarity with the processes, proceeding by the apoptose induction. At the same time the dynamics of the thymocyte nuclei lipid exchange in the process of adaptation to the long radiation effect as nonmonotonous metabolic response to low dose impact is characterized for the first time [ru

Mean-variance portfolio selection and efficient frontier for defined contribution pension schemes

DEFF Research Database (Denmark)

Højgaard, Bjarne; Vigna, Elena

We solve a mean-variance portfolio selection problem in the accumulation phase of a defined contribution pension scheme. The efficient frontier, which is found for the 2 asset case as well as the n + 1 asset case, gives the member the possibility to decide his own risk/reward profile. The mean...... as a mean-variance optimization problem. It is shown that the corresponding mean and variance of the final fund belong to the efficient frontier and also the opposite, that each point on the efficient frontier corresponds to a target-based optimization problem. Furthermore, numerical results indicate...... that the largely adopted lifestyle strategy seems to be very far from being efficient in the mean-variance setting....

ASYMMETRY OF MARKET RETURNS AND THE MEAN VARIANCE FRONTIER

OpenAIRE

SENGUPTA, Jati K.; PARK, Hyung S.

1994-01-01

The hypothesis that the skewness and asymmetry have no significant impact on the mean variance frontier is found to be strongly violated by monthly U.S. data over the period January 1965 through December 1974. This result raises serious doubts whether the common market portifolios such as SP 500, value weighted and equal weighted returns can serve as suitable proxies for meanvariance efficient portfolios in the CAPM framework. A new test for assessing the impact of skewness on the variance fr...

Capacity limitations to extract the mean emotion from multiple facial expressions depend on emotion variance.

Science.gov (United States)

Ji, Luyan; Pourtois, Gilles

2018-04-20

We examined the processing capacity and the role of emotion variance in ensemble representation for multiple facial expressions shown concurrently. A standard set size manipulation was used, whereby the sets consisted of 4, 8, or 16 morphed faces each uniquely varying along a happy-angry continuum (Experiment 1) or a neutral-happy/angry continuum (Experiments 2 & 3). Across the three experiments, we reduced the amount of emotion variance in the sets to explore the boundaries of this process. Participants judged the perceived average emotion from each set on a continuous scale. We computed and compared objective and subjective difference scores, using the morph units and post-experiment ratings, respectively. Results of the subjective scores were more consistent than the objective ones across the first two experiments where the variance was relatively large, and revealed each time that increasing set size led to a poorer averaging ability, suggesting capacity limitations in establishing ensemble representations for multiple facial expressions. However, when the emotion variance in the sets was reduced in Experiment 3, both subjective and objective scores remained unaffected by set size, suggesting that the emotion averaging process was unlimited in these conditions. Collectively, these results suggest that extracting mean emotion from a set composed of multiple faces depends on both structural (attentional) and stimulus-related effects. Copyright © 2018 Elsevier Ltd. All rights reserved.

Global Gravity Wave Variances from Aura MLS: Characteristics and Interpretation

Science.gov (United States)

2008-12-01

slight longitudinal variations, with secondary high- latitude peaks occurring over Greenland and Europe . As the QBO changes to the westerly phase, the...equatorial GW temperature variances from suborbital data (e.g., Eck- ermann et al. 1995). The extratropical wave variances are generally larger in the...emanating from tropopause altitudes, presumably radiated from tropospheric jet stream in- stabilities associated with baroclinic storm systems that

A New Approach for Predicting the Variance of Random Decrement Functions

DEFF Research Database (Denmark)

Asmussen, J. C.; Brincker, Rune

mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...

Use of genomic models to study genetic control of environmental variance

DEFF Research Database (Denmark)

Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel

2011-01-01

. The genomic model commonly found in the literature, with marker effects affecting mean only, is extended to investigate putative effects at the level of the environmental variance. Two classes of models are proposed and their behaviour, studied using simulated data, indicates that they are capable...... of detecting genetic variation at the level of mean and variance. Implementation is via Markov chain Monte Carlo (McMC) algorithms. The models are compared in terms of a measure of global fit, in their ability to detect QTL effects and in terms of their predictive power. The models are subsequently fitted...... to back fat thickness data in pigs. The analysis of back fat thickness shows that the data support genomic models with effects on the mean but not on the variance. The relative sizes of experiment necessary to detect effects on mean and variance is discussed and an extension of the McMC algorithm...

A New Approach for Predicting the Variance of Random Decrement Functions

DEFF Research Database (Denmark)

Asmussen, J. C.; Brincker, Rune

1998-01-01

mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...

Analysis of latent variance reduction methods in phase space Monte Carlo calculations for 6, 10 and 18 MV photons by using MCNP code

International Nuclear Information System (INIS)

Ezzati, A.O.; Sohrabpour, M.

2013-01-01

In this study, azimuthal particle redistribution (APR), and azimuthal particle rotational splitting (APRS) methods are implemented in MCNPX2.4 source code. First of all, the efficiency of these methods was compared to two tallying methods. The APRS is more efficient than the APR method in track length estimator tallies. However in the energy deposition tally, both methods have nearly the same efficiency. Latent variance reduction factors were obtained for 6, 10 and 18 MV photons as well. The APRS relative efficiency contours were obtained. These obtained contours reveal that by increasing the photon energies, the contours depth and the surrounding areas were further increased. The relative efficiency contours indicated that the variance reduction factor is position and energy dependent. The out of field voxels relative efficiency contours showed that latent variance reduction methods increased the Monte Carlo (MC) simulation efficiency in the out of field voxels. The APR and APRS average variance reduction factors had differences less than 0.6% for splitting number of 1000. -- Highlights: ► The efficiency of APR and APRS methods was compared to two tallying methods. ► The APRS is more efficient than the APR method in track length estimator tallies. ► In the energy deposition tally, both methods have nearly the same efficiency. ► Variance reduction factors of these methods are position and energy dependent.

Loschmidt echo for local perturbations: non-monotonic cross-over from the Fermi-golden-rule to the escape-rate regime

International Nuclear Information System (INIS)

Goussev, Arseni; Waltner, Daniel; Richter, Klaus; Jalabert, Rodolfo A

2008-01-01

We address the sensitivity of quantum mechanical time evolution by considering the time decay of the Loschmidt echo (LE) (or fidelity) for local perturbations of the Hamiltonian. Within a semiclassical approach, we derive analytical expressions for the LE decay for chaotic systems for the whole range from weak to strong local perturbations and identify different decay regimes which complement those known for the case of global perturbations. For weak perturbations, a Fermi-golden-rule (FGR)-type behavior is recovered. For strong perturbations, the escape-rate regime is reached, where the LE decays exponentially with a rate independent of the perturbation strength. The transition between the FGR regime and the escape-rate regime is non-monotonic, i.e. the rate of the exponential time-decay of the LE oscillates as a function of the perturbation strength. We further perform extensive quantum mechanical calculations of the LE based on numerical wave packet evolution, which strongly support our semiclassical theory. Finally, we discuss in some detail possible experimental realizations for observing the predicted behavior of the LE

Some novel inequalities for fuzzy variables on the variance and its rational upper bound

Directory of Open Access Journals (Sweden)

Xiajie Yi

2016-02-01

Full Text Available Abstract Variance is of great significance in measuring the degree of deviation, which has gained extensive usage in many fields in practical scenarios. The definition of the variance on the basis of the credibility measure was first put forward in 2002. Following this idea, the calculation of the accurate value of the variance for some special fuzzy variables, like the symmetric and asymmetric triangular fuzzy numbers and the Gaussian fuzzy numbers, is presented in this paper, which turns out to be far more complicated. Thus, in order to better implement variance in real-life projects like risk control and quality management, we suggest a rational upper bound of the variance based on an inequality, together with its calculation formula, which can largely simplify the calculation process within a reasonable range. Meanwhile, some discussions between the variance and its rational upper bound are presented to show the rationality of the latter. Furthermore, two inequalities regarding the rational upper bound of variance and standard deviation of the sum of two fuzzy variables and their individual variances and standard deviations are proved. Subsequently, some numerical examples are illustrated to show the effectiveness and the feasibility of the proposed inequalities.

A class of multi-period semi-variance portfolio for petroleum exploration and development

Science.gov (United States)

Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei

2012-10-01

Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.

Bayesian evaluation of constrained hypotheses on variances of multiple independent groups

NARCIS (Netherlands)

Böing-Messing, F.; van Assen, M.A.L.M.; Hofman, A.D.; Hoijtink, H.; Mulder, J.

2017-01-01

Research has shown that independent groups often differ not only in their means, but also in their variances. Comparing and testing variances is therefore of crucial importance to understand the effect of a grouping variable on an outcome variable. Researchers may have specific expectations

Analysis of conditional genetic effects and variance components in developmental genetics.

Science.gov (United States)

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Development of a treatability variance guidance document for US DOE mixed-waste streams

International Nuclear Information System (INIS)

Scheuer, N.; Spikula, R.; Harms, T.

1990-03-01

In response to the US Department of Energy's (DOE's) anticipated need for variances from the Resource Conservation and Recovery Act (RCRA) Land Disposal Restrictions (LDRs), a treatability variance guidance document was prepared. The guidance manual is for use by DOE facilities and operations offices. The manual was prepared as a part of an ongoing effort by DOE-EH to provide guidance for the operations offices and facilities to comply with the RCRA (LDRs). A treatability variance is an alternative treatment standard granted by EPA for a restricted waste. Such a variance is not an exemption from the requirements of the LDRs, but rather is an alternative treatment standard that must be met before land disposal. The manual, Guidance For Obtaining Variance From the Treatment Standards of the RCRA Land Disposal Restrictions (1), leads the reader through the process of evaluating whether a variance from the treatment standard is a viable approach and through the data-gathering and data-evaluation processes required to develop a petition requesting a variance. The DOE review and coordination process is also described and model language for use in petitions for DOE radioactive mixed waste (RMW) is provided. The guidance manual focuses on RMW streams, however the manual also is applicable to nonmixed, hazardous waste streams. 4 refs

The problem of low variance voxels in statistical parametric mapping; a new hat avoids a 'haircut'.

Science.gov (United States)

Ridgway, Gerard R; Litvak, Vladimir; Flandin, Guillaume; Friston, Karl J; Penny, Will D

2012-02-01

Statistical parametric mapping (SPM) locates significant clusters based on a ratio of signal to noise (a 'contrast' of the parameters divided by its standard error) meaning that very low noise regions, for example outside the brain, can attain artefactually high statistical values. Similarly, the commonly applied preprocessing step of Gaussian spatial smoothing can shift the peak statistical significance away from the peak of the contrast and towards regions of lower variance. These problems have previously been identified in positron emission tomography (PET) (Reimold et al., 2006) and voxel-based morphometry (VBM) (Acosta-Cabronero et al., 2008), but can also appear in functional magnetic resonance imaging (fMRI) studies. Additionally, for source-reconstructed magneto- and electro-encephalography (M/EEG), the problems are particularly severe because sparsity-favouring priors constrain meaningfully large signal and variance to a small set of compactly supported regions within the brain. (Acosta-Cabronero et al., 2008) suggested adding noise to background voxels (the 'haircut'), effectively increasing their noise variance, but at the cost of contaminating neighbouring regions with the added noise once smoothed. Following theory and simulations, we propose to modify--directly and solely--the noise variance estimate, and investigate this solution on real imaging data from a range of modalities. Copyright © 2011 Elsevier Inc. All rights reserved.

Design considerations and analysis planning of a phase 2a proof of concept study in rheumatoid arthritis in the presence of possible non-monotonicity.

Science.gov (United States)

Liu, Feng; Walters, Stephen J; Julious, Steven A

2017-10-02

linear shape curve under fixed dose allocation, no adaptive allocation, half adaptive and adaptive scenarios. The bias though is significantly increased for the Emax model if the true dose response follows a U-shaped curve. In most cases the Bayesian Emax model works effectively and efficiently, with low bias and good probability of success in case of monotonic dose response. However, if there is a belief that the dose response could be non-monotonic then the NDLM is the superior model to assess the dose response.

Variance of a product with application to uranium estimation

International Nuclear Information System (INIS)

Lowe, V.W.; Waterman, M.S.

1976-01-01

The U in a container can either be determined directly by NDA or by estimating the weight of material in the container and the concentration of U in this material. It is important to examine the statistical properties of estimating the amount of U by multiplying the estimates of weight and concentration. The variance of the product determines the accuracy of the estimate of the amount of uranium. This paper examines the properties of estimates of the variance of the product of two random variables

Accounting for non-stationary variance in geostatistical mapping of soil properties

NARCIS (Netherlands)

Wadoux, Alexandre M.J.C.; Brus, Dick J.; Heuvelink, Gerard B.M.

2018-01-01

Simple and ordinary kriging assume a constant mean and variance of the soil variable of interest. This assumption is often implausible because the mean and/or variance are linked to terrain attributes, parent material or other soil forming factors. In kriging with external drift (KED)

The efficiency of the crude oil markets: Evidence from variance ratio tests

Energy Technology Data Exchange (ETDEWEB)

Charles, Amelie, E-mail: acharles@audencia.co [Audencia Nantes, School of Management, 8 route de la Joneliere, 44312 Nantes (France); Darne, Olivier, E-mail: olivier.darne@univ-nantes.f [LEMNA, University of Nantes, IEMN-IAE, Chemin de la Censive du Tertre, 44322 Nantes (France)

2009-11-15

This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable.

The efficiency of the crude oil markets. Evidence from variance ratio tests

International Nuclear Information System (INIS)

Charles, Amelie; Darne, Olivier

2009-01-01

This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable. (author)

The efficiency of the crude oil markets. Evidence from variance ratio tests

Energy Technology Data Exchange (ETDEWEB)

Charles, Amelie [Audencia Nantes, School of Management, 8 route de la Joneliere, 44312 Nantes (France); Darne, Olivier [LEMNA, University of Nantes, IEMN-IAE, Chemin de la Censive du Tertre, 44322 Nantes (France)

2009-11-15

This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable. (author)

Variance reduction methods applied to deep-penetration problems

International Nuclear Information System (INIS)

Cramer, S.N.

1984-01-01

All deep-penetration Monte Carlo calculations require variance reduction methods. Before beginning with a detailed approach to these methods, several general comments concerning deep-penetration calculations by Monte Carlo, the associated variance reduction, and the similarities and differences of these with regard to non-deep-penetration problems will be addressed. The experienced practitioner of Monte Carlo methods will easily find exceptions to any of these generalities, but it is felt that these comments will aid the novice in understanding some of the basic ideas and nomenclature. Also, from a practical point of view, the discussions and developments presented are oriented toward use of the computer codes which are presented in segments of this Monte Carlo course

Cumulative prospect theory and mean variance analysis. A rigorous comparison

OpenAIRE

Hens, Thorsten; Mayer, Janos

2012-01-01

We compare asset allocations derived for cumulative prospect theory(CPT) based on two different methods: Maximizing CPT along the mean–variance efficient frontier and maximizing it without that restriction. We find that with normally distributed returns the difference is negligible. However, using standard asset allocation data of pension funds the difference is considerable. Moreover, with derivatives like call options the restriction to the mean-variance efficient frontier results in a siza...

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

2013-01-01

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

On the mean and variance of the writhe of random polygons

International Nuclear Information System (INIS)

Portillo, J; Scharein, R; Arsuaga, J; Vazquez, M; Diao, Y

2011-01-01

We here address two problems concerning the writhe of random polygons. First, we study the behavior of the mean writhe as a function length. Second, we study the variance of the writhe. Suppose that we are dealing with a set of random polygons with the same length and knot type, which could be the model of some circular DNA with the same topological property. In general, a simple way of detecting chirality of this knot type is to compute the mean writhe of the polygons; if the mean writhe is non-zero then the knot is chiral. How accurate is this method? For example, if for a specific knot type K the mean writhe decreased to zero as the length of the polygons increased, then this method would be limited in the case of long polygons. Furthermore, we conjecture that the sign of the mean writhe is a topological invariant of chiral knots. This sign appears to be the same as that of an 'ideal' conformation of the knot. We provide numerical evidence to support these claims, and we propose a new nomenclature of knots based on the sign of their expected writhes. This nomenclature can be of particular interest to applied scientists. The second part of our study focuses on the variance of the writhe, a problem that has not received much attention in the past. In this case, we focused on the equilateral random polygons. We give numerical as well as analytical evidence to show that the variance of the writhe of equilateral random polygons (of length n) behaves as a linear function of the length of the equilateral random polygon.

On the mean and variance of the writhe of random polygons.

Science.gov (United States)

Portillo, J; Diao, Y; Scharein, R; Arsuaga, J; Vazquez, M

We here address two problems concerning the writhe of random polygons. First, we study the behavior of the mean writhe as a function length. Second, we study the variance of the writhe. Suppose that we are dealing with a set of random polygons with the same length and knot type, which could be the model of some circular DNA with the same topological property. In general, a simple way of detecting chirality of this knot type is to compute the mean writhe of the polygons; if the mean writhe is non-zero then the knot is chiral. How accurate is this method? For example, if for a specific knot type K the mean writhe decreased to zero as the length of the polygons increased, then this method would be limited in the case of long polygons. Furthermore, we conjecture that the sign of the mean writhe is a topological invariant of chiral knots. This sign appears to be the same as that of an "ideal" conformation of the knot. We provide numerical evidence to support these claims, and we propose a new nomenclature of knots based on the sign of their expected writhes. This nomenclature can be of particular interest to applied scientists. The second part of our study focuses on the variance of the writhe, a problem that has not received much attention in the past. In this case, we focused on the equilateral random polygons. We give numerical as well as analytical evidence to show that the variance of the writhe of equilateral random polygons (of length n ) behaves as a linear function of the length of the equilateral random polygon.

Gravity interpretation of dipping faults using the variance analysis method

International Nuclear Information System (INIS)

Essa, Khalid S

2013-01-01

A new algorithm is developed to estimate simultaneously the depth and the dip angle of a buried fault from the normalized gravity gradient data. This algorithm utilizes numerical first horizontal derivatives computed from the observed gravity anomaly, using filters of successive window lengths to estimate the depth and the dip angle of a buried dipping fault structure. For a fixed window length, the depth is estimated using a least-squares sense for each dip angle. The method is based on computing the variance of the depths determined from all horizontal gradient anomaly profiles using the least-squares method for each dip angle. The minimum variance is used as a criterion for determining the correct dip angle and depth of the buried structure. When the correct dip angle is used, the variance of the depths is always less than the variances computed using wrong dip angles. The technique can be applied not only to the true residuals, but also to the measured Bouguer gravity data. The method is applied to synthetic data with and without random errors and two field examples from Egypt and Scotland. In all cases examined, the estimated depths and other model parameters are found to be in good agreement with the actual values. (paper)

Perspective projection for variance pose face recognition from camera calibration

Science.gov (United States)

Fakhir, M. M.; Woo, W. L.; Chambers, J. A.; Dlay, S. S.

2016-04-01

Variance pose is an important research topic in face recognition. The alteration of distance parameters across variance pose face features is a challenging. We provide a solution for this problem using perspective projection for variance pose face recognition. Our method infers intrinsic camera parameters of the image which enable the projection of the image plane into 3D. After this, face box tracking and centre of eyes detection can be identified using our novel technique to verify the virtual face feature measurements. The coordinate system of the perspective projection for face tracking allows the holistic dimensions for the face to be fixed in different orientations. The training of frontal images and the rest of the poses on FERET database determine the distance from the centre of eyes to the corner of box face. The recognition system compares the gallery of images against different poses. The system initially utilises information on position of both eyes then focuses principally on closest eye in order to gather data with greater reliability. Differentiation between the distances and position of the right and left eyes is a unique feature of our work with our algorithm outperforming other state of the art algorithms thus enabling stable measurement in variance pose for each individual.

Estimation of (co)variances for genomic regions of flexible sizes

DEFF Research Database (Denmark)

Sørensen, Lars P; Janss, Luc; Madsen, Per

2012-01-01

was used. There was a clear difference in the region-wise patterns of genomic correlation among combinations of traits, with distinctive peaks indicating the presence of pleiotropic QTL. CONCLUSIONS: The results show that it is possible to estimate, genome-wide and region-wise genomic (co)variances......BACKGROUND: Multi-trait genomic models in a Bayesian context can be used to estimate genomic (co)variances, either for a complete genome or for genomic regions (e.g. per chromosome) for the purpose of multi-trait genomic selection or to gain further insight into the genomic architecture of related...... with a common prior distribution for the marker allele substitution effects and estimation of the hyperparameters in this prior distribution from the progeny means data. From the Markov chain Monte Carlo samples of the allele substitution effects, genomic (co)variances were calculated on a whole-genome level...

Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application

Science.gov (United States)

Zahodne, Laura B.; Manly, Jennifer J.; Brickman, Adam M.; Narkhede, Atul; Griffith, Erica Y.; Guzman, Vanessa A.; Schupf, Nicole; Stern, Yaakov

2016-01-01

Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. PMID:26348002

A study of heterogeneity of environmental variance for slaughter weight in pigs

DEFF Research Database (Denmark)

Ibánez-Escriche, N; Varona, L; Sorensen, D

2008-01-01

This work presents an analysis of heterogeneity of environmental variance for slaughter weight (175 days) in pigs. This heterogeneity is associated with systematic and additive genetic effects. The model also postulates the presence of additive genetic effects affecting the mean and environmental...... variance. The study reveals the presence of genetic variation at the level of the mean and the variance, but an absence of correlation, or a small negative correlation, between both types of additive genetic effects. In addition, we show that both, the additive genetic effects on the mean and those...... on environmental variance have an important influence upon the future economic performance of selected individuals...

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introducea general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive...

Regime shifts in mean-variance efficient frontiers: some international evidence

OpenAIRE

Massimo Guidolin; Federica Ria

2010-01-01

Regime switching models have been assuming a central role in financial applications because of their well-known ability to capture the presence of rich non-linear patterns in the joint distribution of asset returns. This paper examines how the presence of regimes in means, variances, and correlations of asset returns translates into explicit dynamics of the Markowitz mean-variance frontier. In particular, the paper shows both theoretically and through an application to international equity po...

The pricing of long and short run variance and correlation risk in stock returns

NARCIS (Netherlands)

Cosemans, M.

2011-01-01

This paper studies the pricing of long and short run variance and correlation risk. The predictive power of the market variance risk premium for returns is driven by the correlation risk premium and the systematic part of individual variance premia. Furthermore, I find that aggregate volatility risk

A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

Science.gov (United States)

Ben Taieb, Souhaib; Atiya, Amir F

2016-01-01

Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.

Sampling Variances and Covariances of Parameter Estimates in Item Response Theory.

Science.gov (United States)

1982-08-01

substituting (15) into (16) and solving for k and K k = b b1 - o K , (17)k where b and b are means for m and r items, respectively. To find the variance...C5 , and C12 were treated as known. We find that the standard errors of B1 to B5 are increased drastically by ignorance of C 1 to C5 ; all...ERIC Facilltv-Acquisitlons Davie Hall 013A 4833 Rugby Avenue Chapel Hill, NC 27514 Bethesda, MD 20014 -7- Dr. A. J. Eschenbrenner 1 Dr. John R

Variance inflation in high dimensional Support Vector Machines

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2013-01-01

Many important machine learning models, supervised and unsupervised, are based on simple Euclidean distance or orthogonal projection in a high dimensional feature space. When estimating such models from small training sets we face the problem that the span of the training data set input vectors...... the case of Support Vector Machines (SVMS) and we propose a non-parametric scheme to restore proper generalizability. We illustrate the algorithm and its ability to restore performance on a wide range of benchmark data sets....... follow a different probability law with less variance. While the problem and basic means to reconstruct and deflate are well understood in unsupervised learning, the case of supervised learning is less well understood. We here investigate the effect of variance inflation in supervised learning including...

Studying Variance in the Galactic Ultra-compact Binary Population

Science.gov (United States)

Larson, Shane; Breivik, Katelyn

2017-01-01

In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations on week-long timescales, thus allowing a full exploration of the variance associated with a binary stellar evolution model.

Variance estimates for transport in stochastic media by means of the master equation

International Nuclear Information System (INIS)

Pautz, S. D.; Franke, B. C.; Prinja, A. K.

2013-01-01

The master equation has been used to examine properties of transport in stochastic media. It has been shown previously that not only may the Levermore-Pomraning (LP) model be derived from the master equation for a description of ensemble-averaged transport quantities, but also that equations describing higher-order statistical moments may be obtained. We examine in greater detail the equations governing the second moments of the distribution of the angular fluxes, from which variances may be computed. We introduce a simple closure for these equations, as well as several models for estimating the variances of derived transport quantities. We revisit previous benchmarks for transport in stochastic media in order to examine the error of these new variance models. We find, not surprisingly, that the errors in these variance estimates are at least as large as the corresponding estimates of the average, and sometimes much larger. We also identify patterns in these variance estimates that may help guide the construction of more accurate models. (authors)

Markov switching mean-variance frontier dynamics: theory and international evidence

OpenAIRE

M. Guidolin; F. Ria

2010-01-01

It is well-known that regime switching models are able to capture the presence of rich non-linear patterns in the joint distribution of asset returns. After reviewing key concepts and technical issues related to specifying, estimating, and using multivariate Markov switching models in financial applications, in this paper we map the presence of regimes in means, variances, and covariances of asset returns into explicit dynamics of the Markowitz mean-variance frontier. In particular, we show b...

Visual SLAM Using Variance Grid Maps

Science.gov (United States)

Howard, Andrew B.; Marks, Tim K.

2011-01-01

An algorithm denoted Gamma-SLAM performs further processing, in real time, of preprocessed digitized images acquired by a stereoscopic pair of electronic cameras aboard an off-road robotic ground vehicle to build accurate maps of the terrain and determine the location of the vehicle with respect to the maps. Part of the name of the algorithm reflects the fact that the process of building the maps and determining the location with respect to them is denoted simultaneous localization and mapping (SLAM). Most prior real-time SLAM algorithms have been limited in applicability to (1) systems equipped with scanning laser range finders as the primary sensors in (2) indoor environments (or relatively simply structured outdoor environments). The few prior vision-based SLAM algorithms have been feature-based and not suitable for real-time applications and, hence, not suitable for autonomous navigation on irregularly structured terrain. The Gamma-SLAM algorithm incorporates two key innovations: Visual odometry (in contradistinction to wheel odometry) is used to estimate the motion of the vehicle. An elevation variance map (in contradistinction to an occupancy or an elevation map) is used to represent the terrain. The Gamma-SLAM algorithm makes use of a Rao-Blackwellized particle filter (RBPF) from Bayesian estimation theory for maintaining a distribution over poses and maps. The core idea of the RBPF approach is that the SLAM problem can be factored into two parts: (1) finding the distribution over robot trajectories, and (2) finding the map conditioned on any given trajectory. The factorization involves the use of a particle filter in which each particle encodes both a possible trajectory and a map conditioned on that trajectory. The base estimate of the trajectory is derived from visual odometry, and the map conditioned on that trajectory is a Cartesian grid of elevation variances. In comparison with traditional occupancy or elevation grid maps, the grid elevation variance

Genetic and environmental variance in content dimensions of the MMPI.

Science.gov (United States)

Rose, R J

1988-08-01

To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.

Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application.

Science.gov (United States)

Zahodne, Laura B; Manly, Jennifer J; Brickman, Adam M; Narkhede, Atul; Griffith, Erica Y; Guzman, Vanessa A; Schupf, Nicole; Stern, Yaakov

2015-10-01

Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. Copyright © 2015. Published by Elsevier Ltd.

Heritability, variance components and genetic advance of some ...

African Journals Online (AJOL)

Heritability, variance components and genetic advance of some yield and yield related traits in Ethiopian ... African Journal of Biotechnology ... randomized complete block design at Adet Agricultural Research Station in 2008 cropping season.

Modality-Driven Classification and Visualization of Ensemble Variance

Energy Technology Data Exchange (ETDEWEB)

Bensema, Kevin; Gosink, Luke; Obermaier, Harald; Joy, Kenneth I.

2016-10-01

Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no information about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.

The variance of the locally measured Hubble parameter explained with different estimators

DEFF Research Database (Denmark)

Odderskov, Io Sandberg Hess; Hannestad, Steen; Brandbyge, Jacob

2017-01-01

We study the expected variance of measurements of the Hubble constant, H0, as calculated in either linear perturbation theory or using non-linear velocity power spectra derived from N-body simulations. We compare the variance with that obtained by carrying out mock observations in the N......-body simulations, and show that the estimator typically used for the local Hubble constant in studies based on perturbation theory is different from the one used in studies based on N-body simulations. The latter gives larger weight to distant sources, which explains why studies based on N-body simulations tend...... to obtain a smaller variance than that found from studies based on the power spectrum. Although both approaches result in a variance too small to explain the discrepancy between the value of H0 from CMB measurements and the value measured in the local universe, these considerations are important in light...

Variance Risk Premia on Stocks and Bonds

DEFF Research Database (Denmark)

Mueller, Philippe; Sabtchevsky, Petar; Vedolin, Andrea

Investors in fixed income markets are willing to pay a very large premium to be hedged against shocks in expected volatility and the size of this premium can be studied through variance swaps. Using thirty years of option and high-frequency data, we document the following novel stylized facts...

Feasibility of speckle variance OCT for imaging cutaneous microvasculature regeneration during healing of wounds in diabetic mice

Science.gov (United States)

Sharma, P.; Kumawat, J.; Kumar, S.; Sahu, K.; Verma, Y.; Gupta, P. K.; Rao, K. D.

2018-02-01

We report on a study to assess the feasibility of a swept source-based speckle variance optical coherence tomography setup for monitoring cutaneous microvasculature. Punch wounds created in the ear pinnae of diabetic mice were monitored at different times post wounding to assess the structural and vascular changes. It was observed that the epithelium thickness increases post wounding and continues to be thick even after healing. Also, the wound size assessed by vascular images is larger than the physical wound size. The results show that the developed speckle variance optical coherence tomography system can be used to monitor vascular regeneration during wound healing in diabetic mice.

On Mean-Variance Hedging of Bond Options with Stochastic Risk Premium Factor

NARCIS (Netherlands)

Aihara, ShinIchi; Bagchi, Arunabha; Kumar, Suresh K.

2014-01-01

We consider the mean-variance hedging problem for pricing bond options using the yield curve as the observation. The model considered contains infinite-dimensional noise sources with the stochastically- varying risk premium. Hence our model is incomplete. We consider mean-variance hedging under the

Problems of variance reduction in the simulation of random variables

International Nuclear Information System (INIS)

Lessi, O.

1987-01-01

The definition of the uniform linear generator is given and some of the mostly used tests to evaluate the uniformity and the independence of the obtained determinations are listed. The problem of calculating, through simulation, some moment W of a random variable function is taken into account. The Monte Carlo method enables the moment W to be estimated and the estimator variance to be obtained. Some techniques for the construction of other estimators of W with a reduced variance are introduced

Mean-variance portfolio allocation with a value at risk constraint

OpenAIRE

Enrique Sentana

2001-01-01

In this Paper, I first provide a simple unifying approach to static Mean-Variance analysis and Value at Risk, which highlights their similarities and differences. Then I use it to explain how fund managers can take investment decisions that satisfy the VaR restrictions imposed on them by regulators, within the well-known Mean-Variance allocation framework. I do so by introducing a new type of line to the usual mean-standard deviation diagram, called IsoVaR,which represents all the portfolios ...

Variance-based sensitivity analysis for wastewater treatment plant modelling.

Science.gov (United States)

Cosenza, Alida; Mannina, Giorgio; Vanrolleghem, Peter A; Neumann, Marc B

2014-02-01

Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes. © 2013.

Fundamentals of exploratory analysis of variance

CERN Document Server

Hoaglin, David C; Tukey, John W

2009-01-01

The analysis of variance is presented as an exploratory component of data analysis, while retaining the customary least squares fitting methods. Balanced data layouts are used to reveal key ideas and techniques for exploration. The approach emphasizes both the individual observations and the separate parts that the analysis produces. Most chapters include exercises and the appendices give selected percentage points of the Gaussian, t, F chi-squared and studentized range distributions.

On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

Science.gov (United States)

Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

2017-12-01

Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

A new variance stabilizing transformation for gene expression data analysis.

Science.gov (United States)

Kelmansky, Diana M; Martínez, Elena J; Leiva, Víctor

2013-12-01

In this paper, we introduce a new family of power transformations, which has the generalized logarithm as one of its members, in the same manner as the usual logarithm belongs to the family of Box-Cox power transformations. Although the new family has been developed for analyzing gene expression data, it allows a wider scope of mean-variance related data to be reached. We study the analytical properties of the new family of transformations, as well as the mean-variance relationships that are stabilized by using its members. We propose a methodology based on this new family, which includes a simple strategy for selecting the family member adequate for a data set. We evaluate the finite sample behavior of different classical and robust estimators based on this strategy by Monte Carlo simulations. We analyze real genomic data by using the proposed transformation to empirically show how the new methodology allows the variance of these data to be stabilized.

Pricing perpetual American options under multiscale stochastic elasticity of variance

International Nuclear Information System (INIS)

Yoon, Ji-Hun

2015-01-01

Highlights: • We study the effects of the stochastic elasticity of variance on perpetual American option. • Our SEV model consists of a fast mean-reverting factor and a slow mean-revering factor. • A slow scale factor has a very significant impact on the option price. • We analyze option price structures through the market prices of elasticity risk. - Abstract: This paper studies pricing the perpetual American options under a constant elasticity of variance type of underlying asset price model where the constant elasticity is replaced by a fast mean-reverting Ornstein–Ulenbeck process and a slowly varying diffusion process. By using a multiscale asymptotic analysis, we find the impact of the stochastic elasticity of variance on the option prices and the optimal exercise prices with respect to model parameters. Our results enhance the existing option price structures in view of flexibility and applicability through the market prices of elasticity risk

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

International Nuclear Information System (INIS)

Yu, Zhiyong

2013-01-01

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

Energy Technology Data Exchange (ETDEWEB)

Yu, Zhiyong, E-mail: yuzhiyong@sdu.edu.cn [Shandong University, School of Mathematics (China)

2013-12-15

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right.

Genetic and Environmental Variance Among F2 Families in a Commercial Breeding Program for Perennial Ryegrass (Lolium perenne L.)

DEFF Research Database (Denmark)

Fé, Dario; Greve-Pedersen, Morten; Jensen, Christian Sig

2013-01-01

In the joint project “FORAGESELECT”, we aim to implement Genome Wide Selection (GWS) in breeding of perennial ryegrass (Lolium perenne L.), in order to increase genetic response in important agronomic traits such as yield, seed production, stress tolerance and disease resistance, while decreasing...... of this study was to estimate the genetic and environmental variance in the training set composed of F2 families selected from a ten year breeding period. Variance components were estimated on 1193 of those families, sown in 2001, 2003 and 2005 in five locations around Europe. Families were tested together...

Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios

Directory of Open Access Journals (Sweden)

Neslihan Fidan Keçeci

2016-10-01

Full Text Available The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG package, which has precoded modules for optimization with SSD constraints, mean-variance and minimum variance portfolio optimization. We have done in-sample and out-of-sample simulations for portfolios of stocks from the Dow Jones, S&P 100 and DAX indices. The considered portfolios’ SSD dominate the Dow Jones, S&P 100 and DAX indices. Simulation demonstrated a superior performance of portfolios with SD constraints, versus mean-variance and minimum variance portfolios.

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.

Science.gov (United States)

Yang, Ye; Christensen, Ole F; Sorensen, Daniel

2011-02-01

Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

Methods to estimate the between‐study variance and its uncertainty in meta‐analysis†

Science.gov (United States)

Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian PT; Langan, Dean; Salanti, Georgia

2015-01-01

Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically modelled using a between‐study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between‐study variance, has been long challenged. Our aim is to identify known methods for estimation of the between‐study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between‐study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between‐study variance. Based on the scenarios and results presented in the published studies, we recommend the Q‐profile method and the alternative approach based on a ‘generalised Cochran between‐study variance statistic’ to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence‐based recommendations require an extensive simulation study where all methods would be compared under the same scenarios. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. PMID:26332144

Assessing land cover performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis

Science.gov (United States)

Budde, M.E.; Tappan, G.; Rowland, James; Lewis, J.; Tieszen, L.L.

2004-01-01

The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992-93, 1995) and SPOT Vegetation (1998-2001) sensors. We used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. We then summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analysed using Landsat TM imagery and extensive ground knowledge to assess the results. This technique identified anomalies that can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow. Local variance analysis is a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. ?? 2004 Published by Elsevier Ltd.

Genetic variance in micro-environmental sensitivity for milk and milk quality in Walloon Holstein cattle.

Science.gov (United States)

Vandenplas, J; Bastin, C; Gengler, N; Mulder, H A

2013-09-01

Animals that are robust to environmental changes are desirable in the current dairy industry. Genetic differences in micro-environmental sensitivity can be studied through heterogeneity of residual variance between animals. However, residual variance between animals is usually assumed to be homogeneous in traditional genetic evaluations. The aim of this study was to investigate genetic heterogeneity of residual variance by estimating variance components in residual variance for milk yield, somatic cell score, contents in milk (g/dL) of 2 groups of milk fatty acids (i.e., saturated and unsaturated fatty acids), and the content in milk of one individual fatty acid (i.e., oleic acid, C18:1 cis-9), for first-parity Holstein cows in the Walloon Region of Belgium. A total of 146,027 test-day records from 26,887 cows in 747 herds were available. All cows had at least 3 records and a known sire. These sires had at least 10 cows with records and each herd × test-day had at least 5 cows. The 5 traits were analyzed separately based on fixed lactation curve and random regression test-day models for the mean. Estimation of variance components was performed by running iteratively expectation maximization-REML algorithm by the implementation of double hierarchical generalized linear models. Based on fixed lactation curve test-day mean models, heritability for residual variances ranged between 1.01×10(-3) and 4.17×10(-3) for all traits. The genetic standard deviation in residual variance (i.e., approximately the genetic coefficient of variation of residual variance) ranged between 0.12 and 0.17. Therefore, some genetic variance in micro-environmental sensitivity existed in the Walloon Holstein dairy cattle for the 5 studied traits. The standard deviations due to herd × test-day and permanent environment in residual variance ranged between 0.36 and 0.45 for herd × test-day effect and between 0.55 and 0.97 for permanent environmental effect. Therefore, nongenetic effects also

Variance estimation for complex indicators of poverty and inequality using linearization techniques

Directory of Open Access Journals (Sweden)

Guillaume Osier

2009-12-01

Full Text Available The paper presents the Eurostat experience in calculating measures of precision, including standard errors, confidence intervals and design effect coefficients - the ratio of the variance of a statistic with the actual sample design to the variance of that statistic with a simple random sample of same size - for the "Laeken" indicators, that is, a set of complex indicators of poverty and inequality which had been set out in the framework of the EU-SILC project (European Statistics on Income and Living Conditions. The Taylor linearization method (Tepping, 1968; Woodruff, 1971; Wolter, 1985; Tille, 2000 is actually a well-established method to obtain variance estimators for nonlinear statistics such as ratios, correlation or regression coefficients. It consists of approximating a nonlinear statistic with a linear function of the observations by using first-order Taylor Series expansions. Then, an easily found variance estimator of the linear approximation is used as an estimator of the variance of the nonlinear statistic. Although the Taylor linearization method handles all the nonlinear statistics which can be expressed as a smooth function of estimated totals, the approach fails to encompass the "Laeken" indicators since the latter are having more complex mathematical expressions. Consequently, a generalized linearization method (Deville, 1999, which relies on the concept of influence function (Hampel, Ronchetti, Rousseeuw and Stahel, 1986, has been implemented. After presenting the EU-SILC instrument and the main target indicators for which variance estimates are needed, the paper elaborates on the main features of the linearization approach based on influence functions. Ultimately, estimated standard errors, confidence intervals and design effect coefficients obtained from this approach are presented and discussed.

The role of respondents’ comfort for variance in stated choice surveys

DEFF Research Database (Denmark)

Emang, Diana; Lundhede, Thomas; Thorsen, Bo Jellesmark

2017-01-01

they complete surveys correlates with the error variance in stated choice models of their responses. Comfort-related variables are included in the scale functions of the scaled multinomial logit models. The hypothesis was that higher comfort reduces error variance in answers, as revealed by a higher scale...... parameter and vice versa. Information on, e.g., sleep and time since eating (higher comfort) correlated with scale heterogeneity, and produced lower error variance when controlled for in the model. That respondents’ comfort may influence choice behavior suggests that knowledge of the respondents’ activity......Preference elicitation among outdoor recreational users is subject to measurement errors that depend, in part, on survey planning. This study uses data from a choice experiment survey on recreational SCUBA diving to investigate whether self-reported information on respondents’ comfort when...

Design considerations and analysis planning of a phase 2a proof of concept study in rheumatoid arthritis in the presence of possible non-monotonicity

Directory of Open Access Journals (Sweden)

Feng Liu

2017-10-01

follows a placebo like curve, an Emax like curve, or log linear shape curve under fixed dose allocation, no adaptive allocation, half adaptive and adaptive scenarios. The bias though is significantly increased for the Emax model if the true dose response follows a U-shaped curve. Conclusions In most cases the Bayesian Emax model works effectively and efficiently, with low bias and good probability of success in case of monotonic dose response. However, if there is a belief that the dose response could be non-monotonic then the NDLM is the superior model to assess the dose response.

Study on Analysis of Variance on the indigenous wild and cultivated rice species of Manipur Valley

Science.gov (United States)

Medhabati, K.; Rohinikumar, M.; Rajiv Das, K.; Henary, Ch.; Dikash, Th.

2012-10-01

The analysis of variance revealed considerable variation among the cultivars and the wild species for yield and other quantitative characters in both the years of investigation. The highly significant differences among the cultivars in year wise and pooled analysis of variance for all the 12 characters reveal that there are enough genetic variabilities for all the characters studied. The existence of genetic variability is of paramount importance for starting a judicious plant breeding programme. Since introduced high yielding rice cultivars usually do not perform well. Improvement of indigenous cultivars is a clear choice for increase of rice production. The genetic variability of 37 rice germplasms in 12 agronomic characters estimated in the present study can be used in breeding programme

Unraveling the genetic architecture of environmental variance of somatic cell score using high-density single nucleotide polymorphism and cow data from experimental farms.

Science.gov (United States)

Mulder, H A; Crump, R E; Calus, M P L; Veerkamp, R F

2013-01-01

In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean and environmental variance of somatic cell score (SCS) by identifying genome-wide associations for mean and environmental variance of SCS in dairy cows and by quantifying the accuracy of genome-wide breeding values. Somatic cell score was used because previous research has shown that the environmental variance of SCS is partly under genetic control and reduction of the variance of SCS by selection is desirable. In this study, we used 37,590 single nucleotide polymorphism (SNP) genotypes and 46,353 test-day records of 1,642 cows at experimental research farms in 4 countries in Europe. We used a genomic relationship matrix in a double hierarchical generalized linear model to estimate genome-wide breeding values and genetic parameters. The estimated mean and environmental variance per cow was used in a Bayesian multi-locus model to identify SNP associated with either the mean or the environmental variance of SCS. Based on the obtained accuracy of genome-wide breeding values, 985 and 541 independent chromosome segments affecting the mean and environmental variance of SCS, respectively, were identified. Using a genomic relationship matrix increased the accuracy of breeding values relative to using a pedigree relationship matrix. In total, 43 SNP were significantly associated with either the mean (22) or the environmental variance of SCS (21). The SNP with the highest Bayes factor was on chromosome 9 (Hapmap31053-BTA-111664) explaining approximately 3% of the genetic variance of the environmental variance of SCS. Other significant SNP explained less than 1% of the genetic variance. It can be concluded that fewer genomic regions affect the environmental variance of SCS than the

Automated variance reduction of Monte Carlo shielding calculations using the discrete ordinates adjoint function

International Nuclear Information System (INIS)

Wagner, J.C.; Haghighat, A.

1998-01-01

Although the Monte Carlo method is considered to be the most accurate method available for solving radiation transport problems, its applicability is limited by its computational expense. Thus, biasing techniques, which require intuition, guesswork, and iterations involving manual adjustments, are employed to make reactor shielding calculations feasible. To overcome this difficulty, the authors have developed a method for using the S N adjoint function for automated variance reduction of Monte Carlo calculations through source biasing and consistent transport biasing with the weight window technique. They describe the implementation of this method into the standard production Monte Carlo code MCNP and its application to a realistic calculation, namely, the reactor cavity dosimetry calculation. The computational effectiveness of the method, as demonstrated through the increase in calculational efficiency, is demonstrated and quantified. Important issues associated with this method and its efficient use are addressed and analyzed. Additional benefits in terms of the reduction in time and effort required of the user are difficult to quantify but are possibly as important as the computational efficiency. In general, the automated variance reduction method presented is capable of increases in computational performance on the order of thousands, while at the same time significantly reducing the current requirements for user experience, time, and effort. Therefore, this method can substantially increase the applicability and reliability of Monte Carlo for large, real-world shielding applications

Fluctuations in atomic collision cascades - variance and correlations in sputtering and defect distributions

International Nuclear Information System (INIS)

Chakarova, R.; Pazsit, I.

1997-01-01

Fluctuation phenomena are investigated in various collision processes, i.e. ion bombardment induced sputtering and defect creation. The mean and variance of the sputter yield and the vacancies and interstitials are calculated as functions of the ion energy and the ion-target mass ratio. It is found that the relative variance of the defects in half-spaces and the relative variance of the sputter yield are not monotonous functions of the mass ratio. Two-point correlation functions in the depth variable, as well as sputtered energy, are also calculated. These functions help interpreting the behaviour of the relative variances of the integrated quantities, as well as understanding the cascade dynamics. All calculations are based on Lindhard power-law cross sections and use a binary collision Monte Carlo algorithm. 30 refs, 25 figs

Fluctuations in atomic collision cascades - variance and correlations in sputtering and defect distributions

Energy Technology Data Exchange (ETDEWEB)

Chakarova, R.; Pazsit, I.

1997-01-01

Fluctuation phenomena are investigated in various collision processes, i.e. ion bombardment induced sputtering and defect creation. The mean and variance of the sputter yield and the vacancies and interstitials are calculated as functions of the ion energy and the ion-target mass ratio. It is found that the relative variance of the defects in half-spaces and the relative variance of the sputter yield are not monotonous functions of the mass ratio. Two-point correlation functions in the depth variable, as well as sputtered energy, are also calculated. These functions help interpreting the behaviour of the relative variances of the integrated quantities, as well as understanding the cascade dynamics. All calculations are based on Lindhard power-law cross sections and use a binary collision Monte Carlo algorithm. 30 refs, 25 figs.

On discrete stochastic processes with long-lasting time dependence in the variance

Science.gov (United States)

Queirós, S. M. D.

2008-11-01

In this manuscript, we analytically and numerically study statistical properties of an heteroskedastic process based on the celebrated ARCH generator of random variables whose variance is defined by a memory of qm-exponencial, form (eqm=1 x=ex). Specifically, we inspect the self-correlation function of squared random variables as well as the kurtosis. In addition, by numerical procedures, we infer the stationary probability density function of both of the heteroskedastic random variables and the variance, the multiscaling properties, the first-passage times distribution, and the dependence degree. Finally, we introduce an asymmetric variance version of the model that enables us to reproduce the so-called leverage effect in financial markets.

A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2011-01-01

Small sample high-dimensional principal component analysis (PCA) suffers from variance inflation and lack of generalizability. It has earlier been pointed out that a simple leave-one-out variance renormalization scheme can cure the problem. In this paper we generalize the cure in two directions......: First, we propose a computationally less intensive approximate leave-one-out estimator, secondly, we show that variance inflation is also present in kernel principal component analysis (kPCA) and we provide a non-parametric renormalization scheme which can quite efficiently restore generalizability in kPCA....... As for PCA our analysis also suggests a simplified approximate expression. © 2011 Trine J. Abrahamsen and Lars K. Hansen....

Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

Science.gov (United States)

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

Analysis of force variance for a continuous miner drum using the Design of Experiments method

Energy Technology Data Exchange (ETDEWEB)

S. Somanchi; V.J. Kecojevic; C.J. Bise [Pennsylvania State University, University Park, PA (United States)

2006-06-15

Continuous miners (CMs) are excavating machines designed to extract a variety of minerals by underground mining. The variance in force experienced by the cutting drum is a very important aspect that must be considered during drum design. A uniform variance essentially means that an equal load is applied on the individual cutting bits and this, in turn, enables better cutting action, greater efficiency, and longer bit and machine life. There are certain input parameters used in the drum design whose exact relationships with force variance are not clearly understood. This paper determines (1) the factors that have a significant effect on the force variance of the drum and (2) the values that can be assigned to these factors to minimize the force variance. A computer program, Continuous Miner Drum (CMD), was developed in collaboration with Kennametal, Inc. to facilitate the mechanical design of CM drums. CMD also facilitated data collection for determining significant factors affecting force variance. Six input parameters, including centre pitch, outer pitch, balance angle, shift angle, set angle and relative angle were tested at two levels. Trials were configured using the Design of Experiments (DoE) method where 2{sup 6} full-factorial experimental design was selected to investigate the effect of these factors on force variance. Results from the analysis show that all parameters except balance angle, as well as their interactions, significantly affect the force variance.

Thermodynamic equipartition for increased second law efficiency

International Nuclear Information System (INIS)

Thiel, Gregory P.; McGovern, Ronan K.; Zubair, Syed M.; Lienhard V, John H.

2014-01-01

Highlights: • Efficiency gains from equipartition to minimize entropy generation are quantified. • The equipartition factor (Ξ) quantifies the variance of thermodynamic affinities. • Systems with low (Ξ) and low efficiency gain most when redesigned for equipartition. • For lumped capacitance systems long normalized charging times correlate with low (Ξ). - Abstract: In this work, a clear distinction is drawn between irreversibility associated with a finite mean driving force in a transport process and irreversibility associated with variance in the spatial and/or temporal distribution of this driving force. The portion of irreversibility associated with driving force variance is quantified via a newly defined dimensionless quantity, the equipartition factor. This equipartition factor, related to the variance in dimensionless driving force throughout the system, is employed to formulate an expression for second law efficiency. Consequently, the equipartition factor may be employed to identify the improvement in efficiency achievable via system redesign for a reduction in driving force variance, while holding fixed the system output for fixed system dimensions in time and space. It is shown that systems with low second law efficiency and low equipartition factor will have the greatest benefit from a redesign to obtain equipartition. The utility of the equipartition factor in identifying situations where efficiency can be increased without requiring a spatial or temporal increase in system size is illustrated through its application to several simple systems

78 FR 14122 - Revocation of Permanent Variances

Science.gov (United States)

2013-03-04

... Douglas Fir planking had to have at least a 1,900 fiber stress and 1,900,000 modulus of elasticity, while the Yellow Pine planking had to have at least 2,500 fiber stress and 2,000,000 modulus of elasticity... the permanent variances, and affected employees, to submit written data, views, and arguments...

Optimal control of LQG problem with an explicit trade-off between mean and variance

Science.gov (United States)

Qian, Fucai; Xie, Guo; Liu, Ding; Xie, Wenfang

2011-12-01

For discrete-time linear-quadratic Gaussian (LQG) control problems, a utility function on the expectation and the variance of the conventional performance index is considered. The utility function is viewed as an overall objective of the system and can perform the optimal trade-off between the mean and the variance of performance index. The nonlinear utility function is first converted into an auxiliary parameters optimisation problem about the expectation and the variance. Then an optimal closed-loop feedback controller for the nonseparable mean-variance minimisation problem is designed by nonlinear mathematical programming. Finally, simulation results are given to verify the algorithm's effectiveness obtained in this article.

Deterministic mean-variance-optimal consumption and investment

DEFF Research Database (Denmark)

Christiansen, Marcus; Steffensen, Mogens

2013-01-01

In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature that the consum......In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature...... that the consumption rate and the investment proportion are constrained to be deterministic processes. As a result we get rid of a series of unwanted features of the stochastic solution including diffusive consumption, satisfaction points and consistency problems. Deterministic strategies typically appear in unit......-linked life insurance contracts, where the life-cycle investment strategy is age dependent but wealth independent. We explain how optimal deterministic strategies can be found numerically and present an example from life insurance where we compare the optimal solution with suboptimal deterministic strategies...

Variance estimation in the analysis of microarray data

KAUST Repository

Wang, Yuedong; Ma, Yanyuan; Carroll, Raymond J.

2009-01-01

Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing

AN ADAPTIVE OPTIMAL KALMAN FILTER FOR STOCHASTIC VIBRATION CONTROL SYSTEM WITH UNKNOWN NOISE VARIANCES

Institute of Scientific and Technical Information of China (English)

Li Shu; Zhuo Jiashou; Ren Qingwen

2000-01-01

In this paper, an optimal criterion is presented for adaptive Kalman filter in a control sys tem with unknown variances of stochastic vibration by constructing a function of noise variances and minimizing the function. We solve the model and measure variances by using DFP optimal method to guarantee the results of Kalman filter to be optimized. Finally, the control of vibration can be implemented by LQG method.

Filtering for increased power for microarray data analysis

Directory of Open Access Journals (Sweden)

Hess Ann M

2009-01-01

Full Text Available Abstract Background Due to the large number of hypothesis tests performed during the process of routine analysis of microarray data, a multiple testing adjustment is certainly warranted. However, when the number of tests is very large and the proportion of differentially expressed genes is relatively low, the use of a multiple testing adjustment can result in very low power to detect those genes which are truly differentially expressed. Filtering allows for a reduction in the number of tests and a corresponding increase in power. Common filtering methods include filtering by variance, average signal or MAS detection call (for Affymetrix arrays. We study the effects of filtering in combination with the Benjamini-Hochberg method for false discovery rate control and q-value for false discovery rate estimation. Results Three case studies are used to compare three different filtering methods in combination with the two false discovery rate methods and three different preprocessing methods. For the case studies considered, filtering by detection call and variance (on the original scale consistently led to an increase in the number of differentially expressed genes identified. On the other hand, filtering by variance on the log2 scale had a detrimental effect when paired with MAS5 or PLIER preprocessing methods, even when the testing was done on the log2 scale. A simulation study was done to further examine the effect of filtering by variance. We find that filtering by variance leads to higher power, often with a decrease in false discovery rate, when paired with either of the false discovery rate methods considered. This holds regardless of the proportion of genes which are differentially expressed or whether we assume dependence or independence among genes. Conclusion The case studies show that both detection call and variance filtering are viable methods of filtering which can increase the number of differentially expressed genes identified. The

Some asymptotic theory for variance function smoothing | Kibua ...

African Journals Online (AJOL)

Simple selection of the smoothing parameter is suggested. Both homoscedastic and heteroscedastic regression models are considered. Keywords: Asymptotic, Smoothing, Kernel, Bandwidth, Bias, Variance, Mean squared error, Homoscedastic, Heteroscedastic. > East African Journal of Statistics Vol. 1 (1) 2005: pp. 9-22 ...

Properties of realized variance under alternative sampling schemes

NARCIS (Netherlands)

Oomen, R.C.A.

2006-01-01

This paper investigates the statistical properties of the realized variance estimator in the presence of market microstructure noise. Different from the existing literature, the analysis relies on a pure jump process for high frequency security prices and explicitly distinguishes among alternative

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation

DEFF Research Database (Denmark)

Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel

2011-01-01

of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box–Cox transformations. Litter size data in rabbits and pigs that had previously been analysed...... in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box–Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis...... in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected...

Right on Target, or Is it? The Role of Distributional Shape in Variance Targeting

Directory of Open Access Journals (Sweden)

Stanislav Anatolyev

2015-08-01

Full Text Available Estimation of GARCH models can be simplified by augmenting quasi-maximum likelihood (QML estimation with variance targeting, which reduces the degree of parameterization and facilitates estimation. We compare the two approaches and investigate, via simulations, how non-normality features of the return distribution affect the quality of estimation of the volatility equation and corresponding value-at-risk predictions. We find that most GARCH coefficients and associated predictions are more precisely estimated when no variance targeting is employed. Bias properties are exacerbated for a heavier-tailed distribution of standardized returns, while the distributional asymmetry has little or moderate impact, these phenomena tending to be more pronounced under variance targeting. Some effects further intensify if one uses ML based on a leptokurtic distribution in place of normal QML. The sample size has also a more favorable effect on estimation precision when no variance targeting is used. Thus, if computational costs are not prohibitive, variance targeting should probably be avoided.

Variance analysis refines overhead cost control.

Science.gov (United States)

Cooper, J C; Suver, J D

1992-02-01

Many healthcare organizations may not fully realize the benefits of standard cost accounting techniques because they fail to routinely report volume variances in their internal reports. If overhead allocation is routinely reported on internal reports, managers can determine whether billing remains current or lost charges occur. Healthcare organizations' use of standard costing techniques can lead to more realistic performance measurements and information system improvements that alert management to losses from unrecovered overhead in time for corrective action.

Geometric representation of the mean-variance-skewness portfolio frontier based upon the shortage function

OpenAIRE

Kerstens, Kristiaan; Mounier, Amine; Van de Woestyne, Ignace

2008-01-01

The literature suggests that investors prefer portfolios based on mean, variance and skewness rather than portfolios based on mean-variance (MV) criteria solely. Furthermore, a small variety of methods have been proposed to determine mean-variance-skewness (MVS) optimal portfolios. Recently, the shortage function has been introduced as a measure of efficiency, allowing to characterize MVS optimalportfolios using non-parametric mathematical programming tools. While tracing the MV portfolio fro...

Improved estimation of the variance in Monte Carlo criticality calculations

International Nuclear Information System (INIS)

Hoogenboom, J. Eduard

2008-01-01

Results for the effective multiplication factor in a Monte Carlo criticality calculations are often obtained from averages over a number of cycles or batches after convergence of the fission source distribution to the fundamental mode. Then the standard deviation of the effective multiplication factor is also obtained from the k eff results over these cycles. As the number of cycles will be rather small, the estimate of the variance or standard deviation in k eff will not be very reliable, certainly not for the first few cycles after source convergence. In this paper the statistics for k eff are based on the generation of new fission neutron weights during each history in a cycle. It is shown that this gives much more reliable results for the standard deviation even after a small number of cycles. Also attention is paid to the variance of the variance (VoV) and the standard deviation of the standard deviation. A derivation is given how to obtain an unbiased estimate for the VoV, even for a small number of samples. (authors)

Improved estimation of the variance in Monte Carlo criticality calculations

Energy Technology Data Exchange (ETDEWEB)

Hoogenboom, J. Eduard [Delft University of Technology, Delft (Netherlands)

2008-07-01

Results for the effective multiplication factor in a Monte Carlo criticality calculations are often obtained from averages over a number of cycles or batches after convergence of the fission source distribution to the fundamental mode. Then the standard deviation of the effective multiplication factor is also obtained from the k{sub eff} results over these cycles. As the number of cycles will be rather small, the estimate of the variance or standard deviation in k{sub eff} will not be very reliable, certainly not for the first few cycles after source convergence. In this paper the statistics for k{sub eff} are based on the generation of new fission neutron weights during each history in a cycle. It is shown that this gives much more reliable results for the standard deviation even after a small number of cycles. Also attention is paid to the variance of the variance (VoV) and the standard deviation of the standard deviation. A derivation is given how to obtain an unbiased estimate for the VoV, even for a small number of samples. (authors)

A general transform for variance reduction in Monte Carlo simulations

International Nuclear Information System (INIS)

Becker, T.L.; Larsen, E.W.

2011-01-01

This paper describes a general transform to reduce the variance of the Monte Carlo estimate of some desired solution, such as flux or biological dose. This transform implicitly includes many standard variance reduction techniques, including source biasing, collision biasing, the exponential transform for path-length stretching, and weight windows. Rather than optimizing each of these techniques separately or choosing semi-empirical biasing parameters based on the experience of a seasoned Monte Carlo practitioner, this General Transform unites all these variance techniques to achieve one objective: a distribution of Monte Carlo particles that attempts to optimize the desired solution. Specifically, this transform allows Monte Carlo particles to be distributed according to the user's specification by using information obtained from a computationally inexpensive deterministic simulation of the problem. For this reason, we consider the General Transform to be a hybrid Monte Carlo/Deterministic method. The numerical results con rm that the General Transform distributes particles according to the user-specified distribution and generally provide reasonable results for shielding applications. (author)

Multivariate Variance Targeting in the BEKK-GARCH Model

DEFF Research Database (Denmark)

Pedersen, Rasmus Søndergaard; Rahbek, Anders

2014-01-01

This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By definition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modified likelihood function, or estimating function, corresponding...

An entropy approach to size and variance heterogeneity

NARCIS (Netherlands)

Balasubramanyan, L.; Stefanou, S.E.; Stokes, J.R.

2012-01-01

In this paper, we investigate the effect of bank size differences on cost efficiency heterogeneity using a heteroskedastic stochastic frontier model. This model is implemented by using an information theoretic maximum entropy approach. We explicitly model both bank size and variance heterogeneity

Understanding the Degrees of Freedom of Sample Variance by Using Microsoft Excel

Science.gov (United States)

Ding, Jian-Hua; Jin, Xian-Wen; Shuai, Ling-Ying

2017-01-01

In this article, the degrees of freedom of the sample variance are simulated by using the Visual Basic for Applications of Microsoft Excel 2010. The simulation file dynamically displays why the sample variance should be calculated by dividing the sum of squared deviations by n-1 rather than n, which is helpful for students to grasp the meaning of…

Numerical experiment on variance biases and Monte Carlo neutronics analysis with thermal hydraulic feedback

International Nuclear Information System (INIS)

Hyung, Jin Shim; Beom, Seok Han; Chang, Hyo Kim

2003-01-01

Monte Carlo (MC) power method based on the fixed number of fission sites at the beginning of each cycle is known to cause biases in the variances of the k-eigenvalue (keff) and the fission reaction rate estimates. Because of the biases, the apparent variances of keff and the fission reaction rate estimates from a single MC run tend to be smaller or larger than the real variances of the corresponding quantities, depending on the degree of the inter-generational correlation of the sample. We demonstrate this through a numerical experiment involving 100 independent MC runs for the neutronics analysis of a 17 x 17 fuel assembly of a pressurized water reactor (PWR). We also demonstrate through the numerical experiment that Gelbard and Prael's batch method and Ueki et al's covariance estimation method enable one to estimate the approximate real variances of keff and the fission reaction rate estimates from a single MC run. We then show that the use of the approximate real variances from the two-bias predicting methods instead of the apparent variances provides an efficient MC power iteration scheme that is required in the MC neutronics analysis of a real system to determine the pin power distribution consistent with the thermal hydraulic (TH) conditions of individual pins of the system. (authors)

Response variance in functional maps: neural darwinism revisited.

Directory of Open Access Journals (Sweden)

Hirokazu Takahashi

Full Text Available The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.

Response variance in functional maps: neural darwinism revisited.

Science.gov (United States)

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.

Variability of indoor and outdoor VOC measurements: An analysis using variance components

International Nuclear Information System (INIS)

Jia, Chunrong; Batterman, Stuart A.; Relyea, George E.

2012-01-01

This study examines concentrations of volatile organic compounds (VOCs) measured inside and outside of 162 residences in southeast Michigan, U.S.A. Nested analyses apportioned four sources of variation: city, residence, season, and measurement uncertainty. Indoor measurements were dominated by seasonal and residence effects, accounting for 50 and 31%, respectively, of the total variance. Contributions from measurement uncertainty (<20%) and city effects (<10%) were small. For outdoor measurements, season, city and measurement variation accounted for 43, 29 and 27% of variance, respectively, while residence location had negligible impact (<2%). These results show that, to obtain representative estimates of indoor concentrations, measurements in multiple seasons are required. In contrast, outdoor VOC concentrations can use multi-seasonal measurements at centralized locations. Error models showed that uncertainties at low concentrations might obscure effects of other factors. Variance component analyses can be used to interpret existing measurements, design effective exposure studies, and determine whether the instrumentation and protocols are satisfactory. - Highlights: ► The variability of VOC measurements was partitioned using nested analysis. ► Indoor VOCs were primarily controlled by seasonal and residence effects. ► Outdoor VOC levels were homogeneous within neighborhoods. ► Measurement uncertainty was high for many outdoor VOCs. ► Variance component analysis is useful for designing effective sampling programs. - Indoor VOC concentrations were primarily controlled by seasonal and residence effects; and outdoor concentrations were homogeneous within neighborhoods. Variance component analysis is a useful tool for designing effective sampling programs.

Within-category variance and lexical tone discrimination in native and non-native speakers

NARCIS (Netherlands)

Hoffmann, C.W.G.; Sadakata, M.; Chen, A.; Desain, P.W.M.; McQueen, J.M.; Gussenhove, C.; Chen, Y.; Dediu, D.

2014-01-01

In this paper, we show how acoustic variance within lexical tones in disyllabic Mandarin Chinese pseudowords affects discrimination abilities in both native and non-native speakers of Mandarin Chinese. Within-category acoustic variance did not hinder native speakers in discriminating between lexical

Global Distributions of Temperature Variances At Different Stratospheric Altitudes From Gps/met Data

Science.gov (United States)

Gavrilov, N. M.; Karpova, N. V.; Jacobi, Ch.

The GPS/MET measurements at altitudes 5 - 35 km are used to obtain global distribu- tions of small-scale temperature variances at different stratospheric altitudes. Individ- ual temperature profiles are smoothed using second order polynomial approximations in 5 - 7 km thick layers centered at 10, 20 and 30 km. Temperature inclinations from the averaged values and their variances obtained for each profile are averaged for each month of year during the GPS/MET experiment. Global distributions of temperature variances have inhomogeneous structure. Locations and latitude distributions of the maxima and minima of the variances depend on altitudes and season. One of the rea- sons for the small-scale temperature perturbations in the stratosphere could be internal gravity waves (IGWs). Some assumptions are made about peculiarities of IGW gener- ation and propagation in the tropo-stratosphere based on the results of GPS/MET data analysis.

Variance estimation for sensitivity analysis of poverty and inequality measures

Directory of Open Access Journals (Sweden)

Christian Dudel

2017-04-01

Full Text Available Estimates of poverty and inequality are often based on application of a single equivalence scale, despite the fact that a large number of different equivalence scales can be found in the literature. This paper describes a framework for sensitivity analysis which can be used to account for the variability of equivalence scales and allows to derive variance estimates of results of sensitivity analysis. Simulations show that this method yields reliable estimates. An empirical application reveals that accounting for both variability of equivalence scales and sampling variance leads to confidence intervals which are wide.

VARIANCE COMPONENTS AND SELECTION FOR FEATHER PECKING BEHAVIOR IN LAYING HENS

OpenAIRE

Su, Guosheng; Kjaer, Jørgen B.; Sørensen, Poul

2005-01-01

Variance components and selection response for feather pecking behaviour were studied by analysing the data from a divergent selection experiment. An investigation show that a Box-Cox transformation with power =-0.2 made the data be approximately normally distributed and fit best by the given model. Variance components and selection response were estimated using Bayesian analysis with Gibbs sampling technique. The total variation was rather large for the two traits in both low feather peckin...

Asymptotics of variance of the lattice point count

Czech Academy of Sciences Publication Activity Database

Janáček, Jiří

2008-01-01

Roč. 58, č. 3 (2008), s. 751-758 ISSN 0011-4642 R&D Projects: GA AV ČR(CZ) IAA100110502 Institutional research plan: CEZ:AV0Z50110509 Keywords : point lattice * variance Subject RIV: BA - General Mathematics Impact factor: 0.210, year: 2008

Bounds for Tail Probabilities of the Sample Variance

Directory of Open Access Journals (Sweden)

Van Zuijlen M

2009-01-01

Full Text Available We provide bounds for tail probabilities of the sample variance. The bounds are expressed in terms of Hoeffding functions and are the sharpest known. They are designed having in mind applications in auditing as well as in processing data related to environment.

Multivariate Variance Targeting in the BEKK-GARCH Model

DEFF Research Database (Denmark)

Pedersen, Rasmus Søndergaard; Rahbek, Anders

This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By de…nition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modi…ed likelihood function, or estimating function, corresponding...

Age Differences in the Variance of Personality Characteristics

Czech Academy of Sciences Publication Activity Database

Mottus, R.; Allik, J.; Hřebíčková, Martina; Kööts-Ausmees, L.; Realo, A.

2016-01-01

Roč. 30, č. 1 (2016), s. 4-11 ISSN 0890-2070 R&D Projects: GA ČR GA13-25656S Institutional support: RVO:68081740 Keywords : variance * individual differences * personality * five-factor model Subject RIV: AN - Psychology Impact factor: 3.707, year: 2016

Adaptation to Variance of Stimuli in Drosophila Larva Navigation

Science.gov (United States)

Wolk, Jason; Gepner, Ruben; Gershow, Marc

In order to respond to stimuli that vary over orders of magnitude while also being capable of sensing very small changes, neural systems must be capable of rapidly adapting to the variance of stimuli. We study this adaptation in Drosophila larvae responding to varying visual signals and optogenetically induced fictitious odors using an infrared illuminated arena and custom computer vision software. Larval navigational decisions (when to turn) are modeled as the output a linear-nonlinear Poisson process. The development of the nonlinear turn rate in response to changes in variance is tracked using an adaptive point process filter determining the rate of adaptation to different stimulus profiles. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

PORTFOLIO COMPOSITION WITH MINIMUM VARIANCE: COMPARISON WITH MARKET BENCHMARKS

Directory of Open Access Journals (Sweden)

Daniel Menezes Cavalcante

2016-07-01

Full Text Available Portfolio optimization strategies are advocated as being able to allow the composition of stocks portfolios that provide returns above market benchmarks. This study aims to determine whether, in fact, portfolios based on the minimum variance strategy, optimized by the Modern Portfolio Theory, are able to achieve earnings above market benchmarks in Brazil. Time series of 36 securities traded on the BM&FBOVESPA have been analyzed in a long period of time (1999-2012, with sample windows of 12, 36, 60 and 120 monthly observations. The results indicated that the minimum variance portfolio performance is superior to market benchmarks (CDI and IBOVESPA in terms of return and risk-adjusted return, especially in medium and long-term investment horizons.

Motor equivalence and structure of variance: multi-muscle postural synergies in Parkinson's disease.

Science.gov (United States)

Falaki, Ali; Huang, Xuemei; Lewis, Mechelle M; Latash, Mark L

2017-07-01

We explored posture-stabilizing multi-muscle synergies with two methods of analysis of multi-element, abundant systems: (1) Analysis of inter-cycle variance; and (2) Analysis of motor equivalence, both quantified within the framework of the uncontrolled manifold (UCM) hypothesis. Data collected in two earlier studies of patients with Parkinson's disease (PD) were re-analyzed. One study compared synergies in the space of muscle modes (muscle groups with parallel scaling of activation) during tasks performed by early-stage PD patients and controls. The other study explored the effects of dopaminergic medication on multi-muscle-mode synergies. Inter-cycle variance and absolute magnitude of the center of pressure displacement across consecutive cycles were quantified during voluntary whole-body sway within the UCM and orthogonal to the UCM space. The patients showed smaller indices of variance within the UCM and motor equivalence compared to controls. The indices were also smaller in the off-drug compared to on-drug condition. There were strong across-subject correlations between the inter-cycle variance within/orthogonal to the UCM and motor equivalent/non-motor equivalent displacements. This study has shown that, at least for cyclical tasks, analysis of variance and analysis of motor equivalence lead to metrics of stability that correlate with each other and show similar effects of disease and medication. These results show, for the first time, intimate links between indices of variance and motor equivalence. They suggest that analysis of motor equivalence, which requires only a handful of trials, could be used broadly in the field of motor disorders to analyze problems with action stability.

Autonomous estimation of Allan variance coefficients of onboard fiber optic gyro

International Nuclear Information System (INIS)

Song Ningfang; Yuan Rui; Jin Jing

2011-01-01

Satellite motion included in gyro output disturbs the estimation of Allan variance coefficients of fiber optic gyro on board. Moreover, as a standard method for noise analysis of fiber optic gyro, Allan variance has too large offline computational effort and data storages to be applied to online estimation. In addition, with the development of deep space exploration, it is urged that satellite requires more autonomy including autonomous fault diagnosis and reconfiguration. To overcome the barriers and meet satellite autonomy, we present a new autonomous method for estimation of Allan variance coefficients including rate ramp, rate random walk, bias instability, angular random walk and quantization noise coefficients. In the method, we calculate differences between angle increments of star sensor and gyro to remove satellite motion from gyro output, and propose a state-space model using nonlinear adaptive filter technique for quantities previously measured from offline data techniques such as the Allan variance method. Simulations show the method correctly estimates Allan variance coefficients, R = 2.7965exp-4 0 /h 2 , K = 1.1714exp-3 0 /h 1.5 , B = 1.3185exp-3 0 /h, N = 5.982exp-4 0 /h 0.5 and Q = 5.197exp-7 0 in real time, and tracks degradation of gyro performance from initail values, R = 0.651 0 /h 2 , K = 0.801 0 /h 1.5 , B = 0.385 0 /h, N = 0.0874 0 /h 0.5 and Q = 8.085exp-5 0 , to final estimations, R = 9.548 0 /h 2 , K = 9.524 0 /h 1.5 , B = 2.234 0 /h, N = 0.5594 0 /h 0.5 and Q = 5.113exp-4 0 , due to gamma radiation in space. The technique proposed here effectively isolates satellite motion, and requires no data storage and any supports from the ground.

The value of travel time variance

OpenAIRE

Fosgerau, Mogens; Engelson, Leonid

2010-01-01

This paper considers the value of travel time variability under scheduling preferences that are de�fined in terms of linearly time-varying utility rates associated with being at the origin and at the destination. The main result is a simple expression for the value of travel time variability that does not depend on the shape of the travel time distribution. The related measure of travel time variability is the variance of travel time. These conclusions apply equally to travellers who can free...

Evolution of sociality by natural selection on variances in reproductive fitness: evidence from a social bee

OpenAIRE

Stevens, Mark I; Hogendoorn, Katja; Schwarz, Michael P

2007-01-01

Abstract Background The Central Limit Theorem (CLT) is a statistical principle that states that as the number of repeated samples from any population increase, the variance among sample means will decrease and means will become more normally distributed. It has been conjectured that the CLT has the potential to provide benefits for group living in some animals via greater predictability in food acquisition, if the number of foraging bouts increases with group size. The potential existence of ...

Prediction of breeding values and selection responses with genetic heterogeneity of environmental variance

NARCIS (Netherlands)

Mulder, H.A.; Bijma, P.; Hill, W.G.

2007-01-01

There is empirical evidence that genotypes differ not only in mean, but also in environmental variance of the traits they affect. Genetic heterogeneity of environmental variance may indicate genetic differences in environmental sensitivity. The aim of this study was to develop a general framework

Vertical velocity variances and Reynold stresses at Brookhaven

DEFF Research Database (Denmark)

Busch, Niels E.; Brown, R.M.; Frizzola, J.A.

1970-01-01

Results of wind tunnel tests of the Brookhaven annular bivane are presented. The energy transfer functions describing the instrument response and the numerical filter employed in the data reduction process have been used to obtain corrected values of the normalized variance of the vertical wind v...

Multivariate Variance Targeting in the BEKK-GARCH Model

DEFF Research Database (Denmark)

Pedersen, Rasmus Søndergaard; Rahbek, Anders

This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By de…nition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modi…ed like- lihood function, or estimating function, corresponding...

Building Respectful Relationships Early: Educating Children on Gender Variance and Sexual Diversity. A Response to Damien Riggs

Science.gov (United States)

Robinson, Kerry H.

2013-01-01

This article, which is a response to Damien Riggs' article, "Heteronormativity in Online Information about Sex: A South Australian Case Study", focuses on three main areas relevant to children's early education in this area. Firstly, it is important to increase parents', educators', and children's awareness of gender variance or gender…

Time Reversal Migration for Passive Sources Using a Maximum Variance Imaging Condition

KAUST Repository

Wang, H.; Alkhalifah, Tariq Ali

2017-01-01

The conventional time-reversal imaging approach for micro-seismic or passive source location is based on focusing the back-propagated wavefields from each recorded trace in a source image. It suffers from strong background noise and limited acquisition aperture, which may create unexpected artifacts and cause error in the source location. To overcome such a problem, we propose a new imaging condition for microseismic imaging, which is based on comparing the amplitude variance in certain windows, and use it to suppress the artifacts as well as find the right location for passive sources. Instead of simply searching for the maximum energy point in the back-propagated wavefield, we calculate the amplitude variances over a window moving in both space and time axis to create a highly resolved passive event image. The variance operation has negligible cost compared with the forward/backward modeling operations, which reveals that the maximum variance imaging condition is efficient and effective. We test our approach numerically on a simple three-layer model and on a piece of the Marmousi model as well, both of which have shown reasonably good results.

Time Reversal Migration for Passive Sources Using a Maximum Variance Imaging Condition

KAUST Repository

Wang, H.

2017-05-26

The conventional time-reversal imaging approach for micro-seismic or passive source location is based on focusing the back-propagated wavefields from each recorded trace in a source image. It suffers from strong background noise and limited acquisition aperture, which may create unexpected artifacts and cause error in the source location. To overcome such a problem, we propose a new imaging condition for microseismic imaging, which is based on comparing the amplitude variance in certain windows, and use it to suppress the artifacts as well as find the right location for passive sources. Instead of simply searching for the maximum energy point in the back-propagated wavefield, we calculate the amplitude variances over a window moving in both space and time axis to create a highly resolved passive event image. The variance operation has negligible cost compared with the forward/backward modeling operations, which reveals that the maximum variance imaging condition is efficient and effective. We test our approach numerically on a simple three-layer model and on a piece of the Marmousi model as well, both of which have shown reasonably good results.

The genetic variance of resistance in M3 lines of rice against leaf blight disease

International Nuclear Information System (INIS)

Mugiono

1979-01-01

Seeds of Pelita I/1 rice variety were irradiated with 20, 30, 40 and 50 krad of gamma rays from a 60 Co source. Plants of M 3 lines were inoculated with bacterial leaf blight, Xanthomonas oryzae (Uzeda and Ishiyama) Downson, using clipping method. The coefficient of genetic variability of resistance against leaf blight disease increased with increasing dose. Highly significant difference in the genetic variance of resistance were found between the treated samples and the control. Dose of 20 krad gave good probability for selection of plants resistant against leaf blight disease. (author)

Excluded-Mean-Variance Neural Decision Analyzer for Qualitative Group Decision Making

Directory of Open Access Journals (Sweden)

Ki-Young Song

2012-01-01

Full Text Available Many qualitative group decisions in professional fields such as law, engineering, economics, psychology, and medicine that appear to be crisp and certain are in reality shrouded in fuzziness as a result of uncertain environments and the nature of human cognition within which the group decisions are made. In this paper we introduce an innovative approach to group decision making in uncertain situations by using a mean-variance neural approach. The key idea of this proposed approach is to compute the excluded mean of individual evaluations and weight it by applying a variance influence function (VIF; this process of weighting the excluded mean by VIF provides an improved result in the group decision making. In this paper, a case study with the proposed excluded-mean-variance approach is also presented. The results of this case study indicate that this proposed approach can improve the effectiveness of qualitative decision making by providing the decision maker with a new cognitive tool to assist in the reasoning process.

Estimation variance bounds of importance sampling simulations in digital communication systems

Science.gov (United States)

Lu, D.; Yao, K.

1991-01-01

In practical applications of importance sampling (IS) simulation, two basic problems are encountered, that of determining the estimation variance and that of evaluating the proper IS parameters needed in the simulations. The authors derive new upper and lower bounds on the estimation variance which are applicable to IS techniques. The upper bound is simple to evaluate and may be minimized by the proper selection of the IS parameter. Thus, lower and upper bounds on the improvement ratio of various IS techniques relative to the direct Monte Carlo simulation are also available. These bounds are shown to be useful and computationally simple to obtain. Based on the proposed technique, one can readily find practical suboptimum IS parameters. Numerical results indicate that these bounding techniques are useful for IS simulations of linear and nonlinear communication systems with intersymbol interference in which bit error rate and IS estimation variances cannot be obtained readily using prior techniques.

On the multiplicity of option prices under CEV with positive elasticity of variance

NARCIS (Netherlands)

Veestraeten, D.

2017-01-01

The discounted stock price under the Constant Elasticity of Variance model is not a martingale when the elasticity of variance is positive. Two expressions for the European call price then arise, namely the price for which put-call parity holds and the price that represents the lowest cost of

On the multiplicity of option prices under CEV with positive elasticity of variance

NARCIS (Netherlands)

Veestraeten, D.

2014-01-01

The discounted stock price under the Constant Elasticity of Variance (CEV) model is a strict local martingale when the elasticity of variance is positive. Two expressions for the European call price then arise, namely the risk-neutral call price and an alternative price that is linked to the unique

The VIX, the Variance Premium, and Expected Returns

DEFF Research Database (Denmark)

Osterrieder, Daniela Maria; Ventosa-Santaulària, Daniel; Vera-Valdés, Eduardo

2018-01-01

. These problems are eliminated if risk is captured by the variance premium (VP) instead; it is unobservable, however. We propose a 2SLS estimator that produces consistent estimates without observing the VP. Using this method, we find a positive risk–return trade-off and long-run return predictability. Our...

Adaptive Nonparametric Variance Estimation for a Ratio Estimator ...

African Journals Online (AJOL)

Kernel estimators for smooth curves require modifications when estimating near end points of the support, both for practical and asymptotic reasons. The construction of such boundary kernels as solutions of variational problem is a difficult exercise. For estimating the error variance of a ratio estimator, we suggest an ...

Compounding approach for univariate time series with nonstationary variances

Science.gov (United States)

Schäfer, Rudi; Barkhofen, Sonja; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich

2015-12-01

A defining feature of nonstationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent variances. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here, we consider two concrete, but diverse, examples of such nonstationary systems: the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end, we extract the relevant time scales by decomposing the time signals into windows and determine the distribution function of the thus obtained local variances.

Robust LOD scores for variance component-based linkage analysis.

Science.gov (United States)

Blangero, J; Williams, J T; Almasy, L

2000-01-01

The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.

Measuring kinetics of complex single ion channel data using mean-variance histograms.

Science.gov (United States)

Patlak, J B

1993-07-01

The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean-variance

A Random Parameter Model for Continuous-Time Mean-Variance Asset-Liability Management

Directory of Open Access Journals (Sweden)

Hui-qiang Ma

2015-01-01

Full Text Available We consider a continuous-time mean-variance asset-liability management problem in a market with random market parameters; that is, interest rate, appreciation rates, and volatility rates are considered to be stochastic processes. By using the theories of stochastic linear-quadratic (LQ optimal control and backward stochastic differential equations (BSDEs, we tackle this problem and derive optimal investment strategies as well as the mean-variance efficient frontier analytically in terms of the solution of BSDEs. We find that the efficient frontier is still a parabola in a market with random parameters. Comparing with the existing results, we also find that the liability does not affect the feasibility of the mean-variance portfolio selection problem. However, in an incomplete market with random parameters, the liability can not be fully hedged.

Testing constancy of unconditional variance in volatility models by misspecification and specification tests

DEFF Research Database (Denmark)

Silvennoinen, Annastiina; Terasvirta, Timo

The topic of this paper is testing the hypothesis of constant unconditional variance in GARCH models against the alternative that the unconditional variance changes deterministically over time. Tests of this hypothesis have previously been performed as misspecification tests after fitting a GARCH...... models. An application to exchange rate returns is included....

Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

Science.gov (United States)

Holmes, John B; Dodds, Ken G; Lee, Michael A

2017-03-02

An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

Track 4: basic nuclear science variance reduction for Monte Carlo criticality simulations. 6. Variational Variance Reduction for Monte Carlo Criticality Calculations

International Nuclear Information System (INIS)

Densmore, Jeffery D.; Larsen, Edward W.

2001-01-01

Recently, it has been shown that the figure of merit (FOM) of Monte Carlo source-detector problems can be enhanced by using a variational rather than a direct functional to estimate the detector response. The direct functional, which is traditionally employed in Monte Carlo simulations, requires an estimate of the solution of the forward problem within the detector region. The variational functional is theoretically more accurate than the direct functional, but it requires estimates of the solutions of the forward and adjoint source-detector problems over the entire phase-space of the problem. In recent work, we have performed Monte Carlo simulations using the variational functional by (a) approximating the adjoint solution deterministically and representing this solution as a function in phase-space and (b) estimating the forward solution using Monte Carlo. We have called this general procedure variational variance reduction (VVR). The VVR method is more computationally expensive per history than traditional Monte Carlo because extra information must be tallied and processed. However, the variational functional yields a more accurate estimate of the detector response. Our simulations have shown that the VVR reduction in variance usually outweighs the increase in cost, resulting in an increased FOM. In recent work on source-detector problems, we have calculated the adjoint solution deterministically and represented this solution as a linear-in-angle, histogram-in-space function. This procedure has several advantages over previous implementations: (a) it requires much less adjoint information to be stored and (b) it is highly efficient for diffusive problems, due to the accurate linear-in-angle representation of the adjoint solution. (Traditional variance-reduction methods perform poorly for diffusive problems.) Here, we extend this VVR method to Monte Carlo criticality calculations, which are often diffusive and difficult for traditional variance-reduction methods

Variance of a potential of mean force obtained using the weighted histogram analysis method.

Science.gov (United States)

Cukier, Robert I

2013-11-27

A potential of mean force (PMF) that provides the free energy of a thermally driven system along some chosen reaction coordinate (RC) is a useful descriptor of systems characterized by complex, high dimensional potential energy surfaces. Umbrella sampling window simulations use potential energy restraints to provide more uniform sampling along a RC so that potential energy barriers that would otherwise make equilibrium sampling computationally difficult can be overcome. Combining the results from the different biased window trajectories can be accomplished using the Weighted Histogram Analysis Method (WHAM). Here, we provide an analysis of the variance of a PMF along the reaction coordinate. We assume that the potential restraints used for each window lead to Gaussian distributions for the window reaction coordinate densities and that the data sampling in each window is from an equilibrium ensemble sampled so that successive points are statistically independent. Also, we assume that neighbor window densities overlap, as required in WHAM, and that further-than-neighbor window density overlap is negligible. Then, an analytic expression for the variance of the PMF along the reaction coordinate at a desired level of spatial resolution can be generated. The variance separates into a sum over all windows with two kinds of contributions: One from the variance of the biased window density normalized by the total biased window density and the other from the variance of the local (for each window's coordinate range) PMF. Based on the desired spatial resolution of the PMF, the former variance can be minimized relative to that from the latter. The method is applied to a model system that has features of a complex energy landscape evocative of a protein with two conformational states separated by a free energy barrier along a collective reaction coordinate. The variance can be constructed from data that is already available from the WHAM PMF construction.

Markov bridges, bisection and variance reduction

DEFF Research Database (Denmark)

Asmussen, Søren; Hobolth, Asger

. In this paper we firstly consider the problem of generating sample paths from a continuous-time Markov chain conditioned on the endpoints using a new algorithm based on the idea of bisection. Secondly we study the potential of the bisection algorithm for variance reduction. In particular, examples are presented......Time-continuous Markov jump processes is a popular modelling tool in disciplines ranging from computational finance and operations research to human genetics and genomics. The data is often sampled at discrete points in time, and it can be useful to simulate sample paths between the datapoints...

Space-partition method for the variance-based sensitivity analysis: Optimal partition scheme and comparative study

International Nuclear Information System (INIS)

Zhai, Qingqing; Yang, Jun; Zhao, Yu

2014-01-01

Variance-based sensitivity analysis has been widely studied and asserted itself among practitioners. Monte Carlo simulation methods are well developed in the calculation of variance-based sensitivity indices but they do not make full use of each model run. Recently, several works mentioned a scatter-plot partitioning method to estimate the variance-based sensitivity indices from given data, where a single bunch of samples is sufficient to estimate all the sensitivity indices. This paper focuses on the space-partition method in the estimation of variance-based sensitivity indices, and its convergence and other performances are investigated. Since the method heavily depends on the partition scheme, the influence of the partition scheme is discussed and the optimal partition scheme is proposed based on the minimized estimator's variance. A decomposition and integration procedure is proposed to improve the estimation quality for higher order sensitivity indices. The proposed space-partition method is compared with the more traditional method and test cases show that it outperforms the traditional one

Modeling the subfilter scalar variance for large eddy simulation in forced isotropic turbulence

Science.gov (United States)

Cheminet, Adam; Blanquart, Guillaume

2011-11-01

Static and dynamic model for the subfilter scalar variance in homogeneous isotropic turbulence are investigated using direct numerical simulations (DNS) of a lineary forced passive scalar field. First, we introduce a new scalar forcing technique conditioned only on the scalar field which allows the fluctuating scalar field to reach a statistically stationary state. Statistical properties, including 2nd and 3rd statistical moments, spectra, and probability density functions of the scalar field have been analyzed. Using this technique, we performed constant density and variable density DNS of scalar mixing in isotropic turbulence. The results are used in an a-priori study of scalar variance models. Emphasis is placed on further studying the dynamic model introduced by G. Balarac, H. Pitsch and V. Raman [Phys. Fluids 20, (2008)]. Scalar variance models based on Bedford and Yeo's expansion are accurate for small filter width but errors arise in the inertial subrange. Results suggest that a constant coefficient computed from an assumed Kolmogorov spectrum is often sufficient to predict the subfilter scalar variance.

Isolating Trait and Method Variance in the Measurement of Callous and Unemotional Traits.

Science.gov (United States)

Paiva-Salisbury, Melissa L; Gill, Andrew D; Stickle, Timothy R

2017-09-01

To examine hypothesized influence of method variance from negatively keyed items in measurement of callous-unemotional (CU) traits, nine a priori confirmatory factor analysis model comparisons of the Inventory of Callous-Unemotional Traits were evaluated on multiple fit indices and theoretical coherence. Tested models included a unidimensional model, a three-factor model, a three-bifactor model, an item response theory-shortened model, two item-parceled models, and three correlated trait-correlated method minus one models (unidimensional, correlated three-factor, and bifactor). Data were self-reports of 234 adolescents (191 juvenile offenders, 43 high school students; 63% male; ages 11-17 years). Consistent with hypotheses, models accounting for method variance substantially improved fit to the data. Additionally, bifactor models with a general CU factor better fit the data compared with correlated factor models, suggesting a general CU factor is important to understanding the construct of CU traits. Future Inventory of Callous-Unemotional Traits analyses should account for method variance from item keying and response bias to isolate trait variance.

Autonomous estimation of Allan variance coefficients of onboard fiber optic gyro

Energy Technology Data Exchange (ETDEWEB)

Song Ningfang; Yuan Rui; Jin Jing, E-mail: rayleing@139.com [School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191 (China)

2011-09-15

Satellite motion included in gyro output disturbs the estimation of Allan variance coefficients of fiber optic gyro on board. Moreover, as a standard method for noise analysis of fiber optic gyro, Allan variance has too large offline computational effort and data storages to be applied to online estimation. In addition, with the development of deep space exploration, it is urged that satellite requires more autonomy including autonomous fault diagnosis and reconfiguration. To overcome the barriers and meet satellite autonomy, we present a new autonomous method for estimation of Allan variance coefficients including rate ramp, rate random walk, bias instability, angular random walk and quantization noise coefficients. In the method, we calculate differences between angle increments of star sensor and gyro to remove satellite motion from gyro output, and propose a state-space model using nonlinear adaptive filter technique for quantities previously measured from offline data techniques such as the Allan variance method. Simulations show the method correctly estimates Allan variance coefficients, R = 2.7965exp-4 {sup 0}/h{sup 2}, K = 1.1714exp-3 {sup 0}/h{sup 1.5}, B = 1.3185exp-3 {sup 0}/h, N = 5.982exp-4 {sup 0}/h{sup 0.5} and Q = 5.197exp-7 {sup 0} in real time, and tracks degradation of gyro performance from initail values, R = 0.651 {sup 0}/h{sup 2}, K = 0.801 {sup 0}/h{sup 1.5}, B = 0.385 {sup 0}/h, N = 0.0874 {sup 0}/h{sup 0.5} and Q = 8.085exp-5 {sup 0}, to final estimations, R = 9.548 {sup 0}/h{sup 2}, K = 9.524 {sup 0}/h{sup 1.5}, B = 2.234 {sup 0}/h, N = 0.5594 {sup 0}/h{sup 0.5} and Q = 5.113exp-4 {sup 0}, due to gamma radiation in space. The technique proposed here effectively isolates satellite motion, and requires no data storage and any supports from the ground.

Genetic factors explain half of all variance in serum eosinophil cationic protein

DEFF Research Database (Denmark)

Elmose, Camilla; Sverrild, Asger; van der Sluis, Sophie

2014-01-01

with variation in serum ECP and to determine the relative proportion of the variation in ECP due to genetic and non-genetic factors, in an adult twin sample. METHODS: A sample of 575 twins, selected through a proband with self-reported asthma, had serum ECP, lung function, airway responsiveness to methacholine......, exhaled nitric oxide, and skin test reactivity, measured. Linear regression analysis and variance component models were used to study factors associated with variation in ECP and the relative genetic influence on ECP levels. RESULTS: Sex (regression coefficient = -0.107, P ... was statistically non-significant (r = -0.11, P = 0.50). CONCLUSION: Around half of all variance in serum ECP is explained by genetic factors. Serum ECP is influenced by sex, BMI, and airway responsiveness. Serum ECP and airway responsiveness seem not to share genetic variance....

Tip displacement variance of manipulator to simultaneous horizontal and vertical stochastic base excitations

International Nuclear Information System (INIS)

Rahi, A.; Bahrami, M.; Rastegar, J.

2002-01-01

The tip displacement variance of an articulated robotic manipulator to simultaneous horizontal and vertical stochastic base excitation is studied. The dynamic equations for an n-links manipulator subjected to both horizontal and vertical stochastic excitations are derived by Lagrangian method and decoupled for small displacement of joints. The dynamic response covariance of the manipulator links is computed in the coordinate frame attached to the base and then the principal variance of tip displacement is determined. Finally, simulation for a two-link planner robotic manipulator under base excitation is developed. Then sensitivity of the principal variance of tip displacement and tip velocity to manipulator configuration, damping, excitation parameters and manipulator links length are investigated

Variance squeezing and entanglement of the XX central spin model

International Nuclear Information System (INIS)

El-Orany, Faisal A A; Abdalla, M Sebawe

2011-01-01

In this paper, we study the quantum properties for a system that consists of a central atom interacting with surrounding spins through the Heisenberg XX couplings of equal strength. Employing the Heisenberg equations of motion we manage to derive an exact solution for the dynamical operators. We consider that the central atom and its surroundings are initially prepared in the excited state and in the coherent spin state, respectively. For this system, we investigate the evolution of variance squeezing and entanglement. The nonclassical effects have been remarked in the behavior of all components of the system. The atomic variance can exhibit revival-collapse phenomenon based on the value of the detuning parameter.

Variance squeezing and entanglement of the XX central spin model

Energy Technology Data Exchange (ETDEWEB)

El-Orany, Faisal A A [Department of Mathematics and Computer Science, Faculty of Science, Suez Canal University, Ismailia (Egypt); Abdalla, M Sebawe, E-mail: m.sebaweh@physics.org [Mathematics Department, College of Science, King Saud University PO Box 2455, Riyadh 11451 (Saudi Arabia)

2011-01-21

In this paper, we study the quantum properties for a system that consists of a central atom interacting with surrounding spins through the Heisenberg XX couplings of equal strength. Employing the Heisenberg equations of motion we manage to derive an exact solution for the dynamical operators. We consider that the central atom and its surroundings are initially prepared in the excited state and in the coherent spin state, respectively. For this system, we investigate the evolution of variance squeezing and entanglement. The nonclassical effects have been remarked in the behavior of all components of the system. The atomic variance can exhibit revival-collapse phenomenon based on the value of the detuning parameter.

Reduction of variance in spectral estimates for correction of ultrasonic aberration.

Science.gov (United States)

Astheimer, Jeffrey P; Pilkington, Wayne C; Waag, Robert C

2006-01-01

A variance reduction factor is defined to describe the rate of convergence and accuracy of spectra estimated from overlapping ultrasonic scattering volumes when the scattering is from a spatially uncorrelated medium. Assuming that the individual volumes are localized by a spherically symmetric Gaussian window and that centers of the volumes are located on orbits of an icosahedral rotation group, the factor is minimized by adjusting the weight and radius of each orbit. Conditions necessary for the application of the variance reduction method, particularly for statistical estimation of aberration, are examined. The smallest possible value of the factor is found by allowing an unlimited number of centers constrained only to be within a ball rather than on icosahedral orbits. Computations using orbits formed by icosahedral vertices, face centers, and edge midpoints with a constraint radius limited to a small multiple of the Gaussian width show that a significant reduction of variance can be achieved from a small number of centers in the confined volume and that this reduction is nearly the maximum obtainable from an unlimited number of centers in the same volume.

Variance of indoor radon concentration: Major influencing factors

Energy Technology Data Exchange (ETDEWEB)

Yarmoshenko, I., E-mail: ivy@ecko.uran.ru [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation); Vasilyev, A.; Malinovsky, G. [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation); Bossew, P. [German Federal Office for Radiation Protection (BfS), Berlin (Germany); Žunić, Z.S. [Institute of Nuclear Sciences “Vinca”, University of Belgrade (Serbia); Onischenko, A.; Zhukovsky, M. [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation)

2016-01-15

Variance of radon concentration in dwelling atmosphere is analysed with regard to geogenic and anthropogenic influencing factors. Analysis includes review of 81 national and regional indoor radon surveys with varying sampling pattern, sample size and duration of measurements and detailed consideration of two regional surveys (Sverdlovsk oblast, Russia and Niška Banja, Serbia). The analysis of the geometric standard deviation revealed that main factors influencing the dispersion of indoor radon concentration over the territory are as follows: area of territory, sample size, characteristics of measurements technique, the radon geogenic potential, building construction characteristics and living habits. As shown for Sverdlovsk oblast and Niška Banja town the dispersion as quantified by GSD is reduced by restricting to certain levels of control factors. Application of the developed approach to characterization of the world population radon exposure is discussed. - Highlights: • Influence of lithosphere and anthroposphere on variance of indoor radon is found. • Level-by-level analysis reduces GSD by a factor of 1.9. • Worldwide GSD is underestimated.

MENENTUKAN PORTOFOLIO OPTIMAL MENGGUNAKAN MODEL CONDITIONAL MEAN VARIANCE

Directory of Open Access Journals (Sweden)

I GEDE ERY NISCAHYANA

2016-08-01

Full Text Available When the returns of stock prices show the existence of autocorrelation and heteroscedasticity, then conditional mean variance models are suitable method to model the behavior of the stocks. In this thesis, the implementation of the conditional mean variance model to the autocorrelated and heteroscedastic return was discussed. The aim of this thesis was to assess the effect of the autocorrelated and heteroscedastic returns to the optimal solution of a portfolio. The margin of four stocks, Fortune Mate Indonesia Tbk (FMII.JK, Bank Permata Tbk (BNLI.JK, Suryamas Dutamakmur Tbk (SMDM.JK dan Semen Gresik Indonesia Tbk (SMGR.JK were estimated by GARCH(1,1 model with standard innovations following the standard normal distribution and the t-distribution.  The estimations were used to construct a portfolio. The portfolio optimal was found when the standard innovation used was t-distribution with the standard deviation of 1.4532 and the mean of 0.8023 consisting of 0.9429 (94% of FMII stock, 0.0473 (5% of  BNLI stock, 0% of SMDM stock, 1% of  SMGR stock.

Mean-Variance-Validation Technique for Sequential Kriging Metamodels

International Nuclear Information System (INIS)

Lee, Tae Hee; Kim, Ho Sung

2010-01-01

The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean 0 validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean 0 validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels

The Theory of Variances in Equilibrium Reconstruction

International Nuclear Information System (INIS)

Zakharov, Leonid E.; Lewandowski, Jerome; Foley, Elizabeth L.; Levinton, Fred M.; Yuh, Howard Y.; Drozdov, Vladimir; McDonald, Darren

2008-01-01

The theory of variances of equilibrium reconstruction is presented. It complements existing practices with information regarding what kind of plasma profiles can be reconstructed, how accurately, and what remains beyond the abilities of diagnostic systems. The σ-curves, introduced by the present theory, give a quantitative assessment of quality of effectiveness of diagnostic systems in constraining equilibrium reconstructions. The theory also suggests a method for aligning the accuracy of measurements of different physical nature

Mean-Variance Analysis in a Multiperiod Setting

OpenAIRE

Frauendorfer, Karl; Siede, Heiko

1997-01-01

Similar to the classical Markowitz approach it is possible to apply a mean-variance criterion to a multiperiod setting to obtain efficient portfolios. To represent the stochastic dynamic characteristics necessary for modelling returns a process of asset returns is discretized with respect to time and space and summarized in a scenario tree. The resulting optimization problem is solved by means of stochastic multistage programming. The optimal solutions show equivalent structural properties as...

Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained.

Directory of Open Access Journals (Sweden)

Ying Wu

2013-03-01

Full Text Available Genome-wide association studies (GWAS have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG, high-density lipoprotein cholesterol (HDL-C, and low-density lipoprotein cholesterol (LDL-C, respectively, in individuals of African American (n = 6,832, East Asian (n = 9,449, and European (n = 10,829 ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 × 10(-4 in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.

Introduction to variance estimation

CERN Document Server

Wolter, Kirk M

2007-01-01

We live in the information age. Statistical surveys are used every day to determine or evaluate public policy and to make important business decisions. Correct methods for computing the precision of the survey data and for making inferences to the target population are absolutely essential to sound decision making. Now in its second edition, Introduction to Variance Estimation has for more than twenty years provided the definitive account of the theory and methods for correct precision calculations and inference, including examples of modern, complex surveys in which the methods have been used successfully. The book provides instruction on the methods that are vital to data-driven decision making in business, government, and academe. It will appeal to survey statisticians and other scientists engaged in the planning and conduct of survey research, and to those analyzing survey data and charged with extracting compelling information from such data. It will appeal to graduate students and university faculty who...

Is fMRI ?noise? really noise? Resting state nuisance regressors remove variance with network structure

OpenAIRE

Bright, Molly G.; Murphy, Kevin

2015-01-01

Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed ...