Appraisal of Surface Hopping as a Tool for Modeling Condensed Phase Linear Absorption Spectra.
Petit, Andrew S; Subotnik, Joseph E
2015-09-01
Whereas surface hopping is usually used to study populations and mean-field dynamics to study coherences, in two recent papers, we described a procedure for calculating dipole-dipole correlation functions (and therefore absorption spectra) directly from ensembles of surface hopping trajectories. We previously applied this method to a handful of one-dimensional model problems intended to mimic the gas phase. In this article, we now benchmark this new procedure on a set of multidimensional model problems intended to mimic the condensed phase and compare our results against other standard semiclassical methods. By comparison, we demonstrate that methods that include only dynamical information from one PES (the standard Kubo approaches) exhibit large discrepancies with the results of exact quantum dynamics. Furthermore, for model problems with nonadiabatic excited state dynamics but no quantized vibrational structure in the spectra, our surface hopping approach performs comparably to using Ehrenfest dynamics to calculate the electronic coherences. That being said, however, when quantized vibrational structures are present in the spectra but the electronic states are uncoupled, performing the dynamics on the mean PES still outperforms our present method. These benchmark results should influence future studies that use ensembles of independent semiclassical trajectories to model linear as well as multidimensional spectra in the condensed phase. PMID:26575927
Hernández S, A., E-mail: h.s.alfonso@gmail.com, E-mail: meduardo2001@hotmail.com; Cano, M. E., E-mail: h.s.alfonso@gmail.com, E-mail: meduardo2001@hotmail.com [Centro Universitario de la Ciénega, Universidad de Guadalajara, Ocotlán, Jalisco (Mexico); Torres-Arenas, J., E-mail: torresare@gmail.com [Division de Ciencias e Ingenierías, Universidad de Guanajuato, León, Guanajuato (Mexico)
2014-11-07
Currently the absorption of electromagnetic radiation by magnetic nanoparticles is studied for biomedical applications of cancer thermotherapy. Several experiments are conduced following the framework of the Rosensweig model, in order to estimate their specific absorption rate. Nevertheless, this linear approximation involves strong simplifications which constrain their accuracy and validity range. The main aim of this work is to incorporate the deviation of the sphericity assumption in particles shapes, to improve the determination of their specific absorption rate. The correction to the effective particles volume is computed as a measure of the apparent amount of magnetic material, interacting with the external AC magnetic field. Preliminary results using the physical properties of Fe3O4 nanoparticles, exhibit an important correction in their estimated specific absorption rate, as a function of the apparent mean particles radius. Indeed, we have observed using a small deviation (6% of the apparent radius), up to 40% of the predicted specific absorption rate by the Rosensweig linear approximation.
Mitri, F G
2016-01-01
A necessary condition for the validity of the linear viscoelastic model for a (passive) polymeric cylinder with an ultrasonic hysteresis-type absorption submerged in a non-viscous fluid requires that the absorption efficiency is positive (Qabs > 0) satisfying the law of the conservation of energy. This condition imposes restrictions on the values attributed to the normalized absorption coefficients for the compressional and shear-wave wavenumbers for each partial-wave mode n. The forbidden values produce negative axial radiation force, absorption and extinction efficiencies, as well as an enhancement of the scattering efficiency, not in agreement with the conservation of energy law. Numerical results for the radiation force, extinction, absorption and scattering efficiencies are performed for three viscoelastic (VE) polymer cylinders immersed in a non-viscous host liquid (i.e. water) with particular emphasis on the shear-wave absorption coefficient of the cylinder, the dimensionless size parameter and the par...
Generation and Active Absorption of 2- and 3-Dimensional Linear Water Waves in Physical Models
Christensen, Morten
different directional wave spectra. The wave generator displacement signals applied in the tests are generated by means of linear digital filtering of Gaussian white noise in the time domain. An absorbing wave generator for 2-D wave facilities (wave channels) is developed. The absorbing wave generator is......-D wave facilities (wave basins) based on a similar principle is developed. A conventional directional wave generator is converted into an absorbing directional wave generator based on this principle and applied to a series of physical model tests. The test results show that the absorbing directional...
Linear and nonlinear optical absorption coefficients of spherical dome shells
Guo, Kangxian; Liu, Guanghui; Huang, Lu; Zheng, Xianyi
2015-08-01
Linear and nonlinear optical absorption coefficients of spherical dome shells are theoretically investigated within analytical wave functions and numerical quantized energy levels. Our results show that the inner radius, the outer radius and the cut-off angle of spherical dome shells have great influences on linear and nonlinear optical absorption coefficients as well as the total optical absorption coefficients. It is found that with the increase of the inner radius and the outer radius, linear and nonlinear optical absorption coefficients exhibit a blueshift and a redshift, respectively. However, with the increase of the cut-off angle, linear and nonlinear optical absorption coefficients do not shift. Besides, the resonant peaks of linear and nonlinear optical absorption coefficients climb up and then decrease with increasing the cut-off angle. The influences of the incident optical intensity on the total optical absorption coefficients are studied. It is found that the bleaching effect occurs at higher incident optical intensity.
Non-linear absorption for concentrated solar energy transport
Jaramillo, O. A; Del Rio, J.A; Huelsz, G [Centro de Investigacion de Energia, UNAM, Temixco, Morelos (Mexico)
2000-07-01
In order to determine the maximum solar energy that can be transported using SiO{sub 2} optical fibers, analysis of non-linear absorption is required. In this work, we model the interaction between solar radiation and the SiO{sub 2} optical fiber core to determine the dependence of the absorption of the radioactive intensity. Using Maxwell's equations we obtain the relation between the refractive index and the electric susceptibility up to second order in terms of the electric field intensity. This is not enough to obtain an explicit expression for the non-linear absorption. Thus, to obtain the non-linear optical response, we develop a microscopic model of an harmonic driven oscillators with damp ing, based on the Drude-Lorentz theory. We solve this model using experimental information for the SiO{sub 2} optical fiber, and we determine the frequency-dependence of the non-linear absorption and the non-linear extinction of SiO{sub 2} optical fibers. Our results estimate that the average value over the solar spectrum for the non-linear extinction coefficient for SiO{sub 2} is k{sub 2}=10{sup -}29m{sup 2}V{sup -}2. With this result we conclude that the non-linear part of the absorption coefficient of SiO{sub 2} optical fibers during the transport of concentrated solar energy achieved by a circular concentrator is negligible, and therefore the use of optical fibers for solar applications is an actual option. [Spanish] Con el objeto de determinar la maxima energia solar que puede transportarse usando fibras opticas de SiO{sub 2} se requiere el analisis de absorcion no linear. En este trabajo modelamos la interaccion entre la radiacion solar y el nucleo de la fibra optica de SiO{sub 2} para determinar la dependencia de la absorcion de la intensidad radioactiva. Mediante el uso de las ecuaciones de Maxwell obtenemos la relacion entre el indice de refraccion y la susceptibilidad electrica hasta el segundo orden en terminos de intensidad del campo electrico. Esto no es
Faraway, Julian J
2014-01-01
A Hands-On Way to Learning Data AnalysisPart of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition.New to the Second EditionReorganiz
Høskuldsson, Agnar
1996-01-01
Determination of the proper dimension of a given linear model is one of the most important tasks in the applied modeling work. We consider here eight criteria that can be used to determine the dimension of the model, or equivalently, the number of components to use in the model. Four of these...... the basic problems in determining the dimension of linear models. Then each of the eight measures are treated. The results are illustrated by examples....
Foundations of linear and generalized linear models
Agresti, Alan
2015-01-01
A valuable overview of the most important ideas and results in statistical analysis Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linear statistical models. The book presents a broad, in-depth overview of the most commonly used statistical models by discussing the theory underlying the models, R software applications, and examples with crafted models to elucidate key ideas and promote practical model building. The book begins by illustrating the fundamentals of linear models,
Linear models: permutation methods
Cade, B.S.
2005-01-01
Permutation tests (see Permutation Based Inference) for the linear model have applications in behavioral studies when traditional parametric assumptions about the error term in a linear model are not tenable. Improved validity of Type I error rates can be achieved with properly constructed permutation tests. Perhaps more importantly, increased statistical power, improved robustness to effects of outliers, and detection of alternative distributional differences can be achieved by coupling permutation inference with alternative linear model estimators. For example, it is well-known that estimates of the mean in linear model are extremely sensitive to even a single outlying value of the dependent variable compared to estimates of the median [7, 19]. Traditionally, linear modeling focused on estimating changes in the center of distributions (means or medians). However, quantile regression allows distributional changes to be estimated in all or any selected part of a distribution or responses, providing a more complete statistical picture that has relevance to many biological questions [6]...
A new active absorption system and its performance to linear and non-linear waves
Andersen, Thomas Lykke; Clavero, M.; Frigaard, Peter Bak; Losada, M.; Puyol, J. I.
Highlights •An active absorption system for wavemakers has been developed. •The theory for flush mounted gauges has been extended to cover also small gaps. •The new system has been validated in a wave flume with wavemakers in both ends. •A generation and absorption procedure for highly non-linear...
Non linear viscoelastic models
Agerkvist, Finn T.
2011-01-01
Viscoelastic eects are often present in loudspeaker suspensions, this can be seen in the displacement transfer function which often shows a frequency dependent value below the resonance frequency. In this paper nonlinear versions of the standard linear solid model (SLS) are investigated. The...
Silver Nanoparticles with Broad Multiband Linear Optical Absorption
Bakr, Osman M.
2009-07-06
A simple one-pot method produces silver nanoparticles coated with aryl thiols that show intense, broad nonplasmonic optical properties. The synthesis works with many aryl-thiol capping ligands, including water-soluble 4-mercaptobenzoic acid. The nanoparticles produced show linear absorption that is broader, stronger, and more structured than most conventional organic and inorganic dyes.
Monahan, John F
2008-01-01
Preface Examples of the General Linear Model Introduction One-Sample Problem Simple Linear Regression Multiple Regression One-Way ANOVA First Discussion The Two-Way Nested Model Two-Way Crossed Model Analysis of Covariance Autoregression Discussion The Linear Least Squares Problem The Normal Equations The Geometry of Least Squares Reparameterization Gram-Schmidt Orthonormalization Estimability and Least Squares Estimators Assumptions for the Linear Mean Model Confounding, Identifiability, and Estimability Estimability and Least Squares Estimators F
Campagnoli, Patrizia; Petris, Giovanni
2009-01-01
State space models have gained tremendous popularity in as disparate fields as engineering, economics, genetics and ecology. Introducing general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. It illustrates the fundamental steps needed to use dynamic linear models in practice, using R package.
Sparse Linear Identifiable Multivariate Modeling
Henao, Ricardo; Winther, Ole
2011-01-01
In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...... Bayesian hierarchy for sparse models using slab and spike priors (two-component δ-function and continuous mixtures), non-Gaussian latent factors and a stochastic search over the ordering of the variables. The framework, which we call SLIM (Sparse Linear Identifiable Multivariate modeling), is validated and...... computational complexity. We attribute this mainly to the stochastic search strategy used, and to parsimony (sparsity and identifiability), which is an explicit part of the model. We propose two extensions to the basic i.i.d. linear framework: non-linear dependence on observed variables, called SNIM (Sparse Non-linear...
Sparse Linear Identifiable Multivariate Modeling
Henao, Ricardo; Winther, Ole
2011-01-01
In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...... Bayesian hierarchy for sparse models using slab and spike priors (two-component δ-function and continuous mixtures), non-Gaussian latent factors and a stochastic search over the ordering of the variables. The framework, which we call SLIM (Sparse Linear Identifiable Multivariate modeling), is validated and......-linear Identifiable Multivariate modeling) and allowing for correlations between latent variables, called CSLIM (Correlated SLIM), for the temporal and/or spatial data. The source code and scripts are available from http://cogsys.imm.dtu.dk/ slim/. © 2011 Ricardo Henao and Ole Winther....
Explorative methods in linear models
Høskuldsson, Agnar
2004-01-01
The author has developed the H-method of mathematical modeling that builds up the model by parts, where each part is optimized with respect to prediction. Besides providing with better predictions than traditional methods, these methods provide with graphic procedures for analyzing different feat...... features in data. These graphic methods extend the well-known methods and results of Principal Component Analysis to any linear model. Here the graphic procedures are applied to linear regression and Ridge Regression....
Fuzzy linear regression forecasting models
吴冲; 惠晓峰; 朱洪文
2002-01-01
The fuzzy linear regression forecasting model is deduced from the symmetric triangular fuzzy number.With the help of the degree of fitting and the measure of fuzziness, the determination of symmetric triangularfuzzy numbers is changed into a problem of solving linear programming.
Generalized, Linear, and Mixed Models
McCulloch, Charles E; Neuhaus, John M
2011-01-01
An accessible and self-contained introduction to statistical models-now in a modernized new editionGeneralized, Linear, and Mixed Models, Second Edition provides an up-to-date treatment of the essential techniques for developing and applying a wide variety of statistical models. The book presents thorough and unified coverage of the theory behind generalized, linear, and mixed models and highlights their similarities and differences in various construction, application, and computational aspects.A clear introduction to the basic ideas of fixed effects models, random effects models, and mixed m
Several letters discuss the short-comings of the use of the linear quadratic model in fractionated radiotherapy and the validity of the prediction of hyperfractionation as the operational strategy for most human tumours. Particular points discussed are the absence of a time factor in the linear quadratic model, corrections in regard to OER and the clinical implications of isoeffect relationships for normal tissue damage. (U.K.)
Decomposable log-linear models
Eriksen, Poul Svante
can be characterized by a structured set of conditional independencies between some variables given some other variables. We term the new model class decomposable log-linear models, which is illustrated to be a much richer class than decomposable graphical models.It covers a wide range of non...
New analytical solution to calculate linear absorption coefficients of beta radiations
The paper deals with an alternative model of beta radiation transmissions through attenuation layers and brings another analytical description of this phenomenon. The model is validated with a reliable data set and brings a possibility to calculate characteristic material parameters with low uncertainties. Using no correction factors, these calculations can be considered fundamental and inspiring for further research in the field. - Highlights: • New analytical model of beta radiation transmission curve in 2π geometry has been proposed. • Linear absorption coefficients in aluminum and Mylar were calculated for 19 radionuclides. • An empirical relationship between the calculated range parameter and average energy of beta radiation emitted by radionuclides was established
Parameterized Linear Longitudinal Airship Model
Kulczycki, Eric; Elfes, Alberto; Bayard, David; Quadrelli, Marco; Johnson, Joseph
2010-01-01
A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics
Johnsen, Kristinn; Jauho, Antti-Pekka
1998-01-01
We theoretically study the effect of THz radiation on the linear optical absorption spectra of semiconductor structures. A general theoretical framework, based on nonequilibrium Green functions, is formulated and applied to the calculation of linear optical absorption spectrum for several nonequi...
Linear Sigma Models with Torsion
Quigley, Callum
2011-01-01
Gauged linear sigma models with (0,2) supersymmetry allow a larger choice of couplings than models with (2,2) supersymmetry. We use this freedom to find a fully linear construction of torsional heterotic compactifications, including models with branes. As a non-compact example, we describe a family of metrics which correspond to deformations of the heterotic conifold by turning on H-flux. We then describe compact models which are gauge-invariant only at the quantum level. Our construction gives a generalization of symplectic reduction. The resulting spaces are non-Kahler analogues of familiar toric spaces like complex projective space. Perturbatively conformal models can be constructed by considering intersections.
Linear modeling of glacier fluctuations
Oerlemans, J.
2012-01-01
In this contribution a linear first-order differential equation is used to model glacier length fluctuations. This equation has two parameters describing the physical characteristics of a glacier: the climate sensitivity, expressing how the equilibrium glacier length depends on the climatic state, a
Modelling Loudspeaker Non-Linearities
Agerkvist, Finn T.
2007-01-01
This paper investigates different techniques for modelling the non-linear parameters of the electrodynamic loudspeaker. The methods are tested not only for their accuracy within the range of original data, but also for the ability to work reasonable outside that range, and it is demonstrated that...
High dimensional linear inverse modelling
Cooper, Fenwick C
2015-01-01
We introduce and demonstrate two linear inverse modelling methods for systems of stochastic ODE's with accuracy that is independent of the dimensionality (number of elements) of the state vector representing the system in question. Truncation of the state space is not required. Instead we rely on the principle that perturbations decay with distance or the fact that for many systems, the state of each data point is only determined at an instant by itself and its neighbours. We further show that all necessary calculations, as well as numerical integration of the resulting linear stochastic system, require computational time and memory proportional to the dimensionality of the state vector.
Tunable Optical Limiting Action due to Non-linear Absorption in ZnO/Ag Nanocomposites
Radhu, S.; Vijayan, C.; Sandeep, Suchand; Philip, Reji
2011-07-01
ZnO/Ag nanocomposites with different silver concentration are successfully synthesized by solvothermal method. The characterization of the as- synthesized samples is done using XRD, UV-visible spectroscopy and HRTEM and the results indicate that the composites consist of silver nanoparticles attached to the ZnO nanoparticles. The optical non-linearity in these samples is studied using open aperture Z-scan technique and the experimental results agree well with a theoretical model involving two- photon absorption. It is found that the parameters of optical limiting can be tuned in a broad band by varying the silver concentration in the samples.
Theory of Linear Optical Absorption in B_12 Clusters: Role of the geometry
Sahu, Sridhar
2009-01-01
Boron clusters have been widely studied theoretically for their geometrical properties and electronic structure using a variety of methodologies. An important cluster of boron is the B$_{12}$ cluster whose two main isomers have distinct geometries, namely, icosahedral ($I_{h}$) and quasi planar ($C_{3v}$). In this paper we investigate the linear optical absorption spectrum of these two B$_{12}$ structures with the aim of examining the role of geometry on the optical properties of clusters. The optical absorption calculations are performed using both the semi-empirical and the ab initio approaches. The semi-empirical approach uses a wave function methodology employing the INDO model Hamiltonian, coupled with large-scale configuration interaction (CI) calculations, to account for the electron-correlation effects. The \\emph{ab initio} calculations are performed within a time-dependent-density-functional-theory (TDDFT) methodology. The results for the two approaches are in very good qualitative agreement with eac...
Time-dependent oral absorption models
Higaki, K.; Yamashita, S.; Amidon, G. L.
2001-01-01
The plasma concentration-time profiles following oral administration of drugs are often irregular and cannot be interpreted easily with conventional models based on first- or zero-order absorption kinetics and lag time. Six new models were developed using a time-dependent absorption rate coefficient, ka(t), wherein the time dependency was varied to account for the dynamic processes such as changes in fluid absorption or secretion, in absorption surface area, and in motility with time, in the gastrointestinal tract. In the present study, the plasma concentration profiles of propranolol obtained in human subjects following oral dosing were analyzed using the newly derived models based on mass balance and compared with the conventional models. Nonlinear regression analysis indicated that the conventional compartment model including lag time (CLAG model) could not predict the rapid initial increase in plasma concentration after dosing and the predicted Cmax values were much lower than that observed. On the other hand, all models with the time-dependent absorption rate coefficient, ka(t), were superior to the CLAG model in predicting plasma concentration profiles. Based on Akaike's Information Criterion (AIC), the fluid absorption model without lag time (FA model) exhibited the best overall fit to the data. The two-phase model including lag time, TPLAG model was also found to be a good model judging from the values of sum of squares. This model also described the irregular profiles of plasma concentration with time and frequently predicted Cmax values satisfactorily. A comparison of the absorption rate profiles also suggested that the TPLAG model is better at prediction of irregular absorption kinetics than the FA model. In conclusion, the incorporation of a time-dependent absorption rate coefficient ka(t) allows the prediction of nonlinear absorption characteristics in a more reliable manner.
Infrared absorption modeling of VOx microbolometer
Aggoun, Mehdi; Jiang, Jianliang; Khan, M. K.
2015-08-01
The absorption model plays an important role in the design of the microbolometer structure regarding the determination of the optimum thickness of the structure layers. Moreover, the infrared absorption depends on the wavelength of the radiation and the material properties. In this paper, we presented an Infrared absorption model with absorption coefficient of 96% at maximum absorption wavelength of 9.89μm which is very close to the expected value 10μm. This model was established by using MATLAB so that the simulation of the infrared absorption of the VOx microbolometer could be accomplished. In order to confirm the role of this modeling in the design of the device structure, comparison with other structures is also studied in this paper.
Willige, van R.W.G.; Linssen, J.P.H.; Voragen, A.G.J.
2000-01-01
The influence of oil and food components in real food products on the absorption of four flavour compounds (limonene, decanal, linalool and ethyl 2-methyl butyrate) into linear low-density polyethylene (LLDPE) was studied using a large volume injection GC in vial extraction method. Model food system
Willige, van R.W.G.; Linssen, J.P.H.; Voragen, A.G.J.
2000-01-01
The influence of oil and food components in real food products on the absorption of four flavour compounds (limonene, decanal, linalool and ethyl 2-methyl butyrate) into linear low-density polyethylene (LLDPE) was studied using a large volume injection GC in vial extraction method. Model food system
Linear Accelerating Superluminal Motion Model
Zhou, J F; Li, T P; Su, Y; Venturi, T
2004-01-01
Accelerating superluminal motions were detected recently by multi-epoch Very Long Baseline Interferometry (VLBI) observations. Here, a Linear Accelerating Superluminal Motion (LASM) model is proposed to interpret the observed phenomena. The model provides a direct and accurate way to estimate the viewing angle of a relativistic jet. It also predicts that both Doppler boosting and deboosting effects may take place in an accelerating forward jet. The LASM model is applied to the data of the quasar 3C 273, and the initial velocity, acceleration and viewing angle of its three components are derived through model fits. The variations of the viewing angle suggest that a supermassive black hole binary system may exist in the center of 3C273. The gap between the inner and outer jet in some radio loud AGNs my be explained in terms of Doppler deboosting effects when the components accelerate to ultra-relativistic speed.
Matrix algebra for linear models
Gruber, Marvin H J
2013-01-01
Matrix methods have evolved from a tool for expressing statistical problems to an indispensable part of the development, understanding, and use of various types of complex statistical analyses. This evolution has made matrix methods a vital part of statistical education. Traditionally, matrix methods are taught in courses on everything from regression analysis to stochastic processes, thus creating a fractured view of the topic. Matrix Algebra for Linear Models offers readers a unique, unified view of matrix analysis theory (where and when necessary), methods, and their applications. Written f
Linear and nonlinear absorption coefficients of two-electron spherical quantum dot (QD) with parabolic potential are investigated in this paper. Wave functions and energy eigenvalues of the 1s2, 1s1p, 1s1d and 1s1f electronic states have been computed by using an optimization approach, which is a combination of Quantum Genetic Algorithm (QGA) and Hartree–Fock Roothaan (HFR) method. It is found that the strength of S→P transition is stronger than P→D and D→F transitions. Also the peak positions and amplitudes of the absorption coefficients are sensitive to the electron spin. It should be noted that the peak positions and amplitudes of absorption coefficients are strongly dependent on the parabolic potential. Additionally, dot radius, impurity charge, incident optical intensity and relaxation time have a great influence on the linear and nonlinear absorption coefficients
Linear and non-linear perturbations in dark energy models
Escamilla-Rivera, Celia; Casarini, Luciano; Fabris, Julio C.; Alcaniz, Jailson S.
2016-01-01
In this work we discuss observational aspects of three time-dependent parameterisations of the dark energy equation of state $w(z)$. In order to determine the dynamics associated with these models, we calculate their background evolution and perturbations in a scalar field representation. After performing a complete treatment of linear perturbations, we also show that the non-linear contribution of the selected $w(z)$ parameterisations to the matter power spectra is almost the same for all sc...
Modeling and solving linear programming with R
Sallán Leyes, José María; Lordan González, Oriol; Fernández Alarcón, Vicenç
2015-01-01
Linear programming is one of the most extensively used techniques in the toolbox of quantitative methods of optimization. One of the reasons of the popularity of linear programming is that it allows to model a large variety of situations with a simple framework. Furthermore, a linear program is relatively easy to solve. The simplex method allows to solve most linear programs efficiently, and the Karmarkar interior-point method allows a more efficient solving of some kinds of linear programmin...
Linear and non-linear perturbations in dark energy models
Escamilla-Rivera, Celia; Fabris, Julio C; Alcaniz, Jailson S
2016-01-01
In this work we discuss observational aspects of three time-dependent parameterisations of the dark energy equation of state $w(z)$. In order to determine the dynamics associated with these models, we calculate their background evolution and perturbations in a scalar field representation. After performing a complete treatment of linear perturbations, we also show that the non-linear contribution of the selected $w(z)$ parameterisations to the matter power spectra is almost the same for all scales, with no significant difference from the predictions of the standard $\\Lambda$CDM model.
Nonlinear Modeling by Assembling Piecewise Linear Models
Yao, Weigang; Liou, Meng-Sing
2013-01-01
To preserve nonlinearity of a full order system over a parameters range of interest, we propose a simple modeling approach by assembling a set of piecewise local solutions, including the first-order Taylor series terms expanded about some sampling states. The work by Rewienski and White inspired our use of piecewise linear local solutions. The assembly of these local approximations is accomplished by assigning nonlinear weights, through radial basis functions in this study. The efficacy of the proposed procedure is validated for a two-dimensional airfoil moving at different Mach numbers and pitching motions, under which the flow exhibits prominent nonlinear behaviors. All results confirm that our nonlinear model is accurate and stable for predicting not only aerodynamic forces but also detailed flowfields. Moreover, the model is robustness-accurate for inputs considerably different from the base trajectory in form and magnitude. This modeling preserves nonlinearity of the problems considered in a rather simple and accurate manner.
The Linear Absorption and Pump-Probe Spectra of Cylindrical Molecular Aggregates
Bednarz, Mariusz; Knoester, Jasper
2001-01-01
We study the optical response of Frenkel excitons in molecular J aggregates with a cylindrical geometry. Such aggregates have recently been prepared for a class of cyanine dyes and are akin to the rod- and ring-shaped light-harvesting systems found in certain bacteria. The linear absorption spectrum
Processing Approach of Non-linear Adjustment Models in the Space of Non-linear Models
LI Chaokui; ZHU Qing; SONG Chengfang
2003-01-01
This paper investigates the mathematic features of non-linear models and discusses the processing way of non-linear factors which contributes to the non-linearity of a nonlinear model. On the basis of the error definition, this paper puts forward a new adjustment criterion, SGPE.Last, this paper investigates the solution of a non-linear regression model in the non-linear model space and makes the comparison between the estimated values in non-linear model space and those in linear model space.
Puķīte, Jānis; Wagner, Thomas
2016-05-01
We address the application of differential optical absorption spectroscopy (DOAS) of scattered light observations in the presence of strong absorbers (in particular ozone), for which the absorption optical depth is a non-linear function of the trace gas concentration. This is the case because Beer-Lambert law generally does not hold for scattered light measurements due to many light paths contributing to the measurement. While in many cases linear approximation can be made, for scenarios with strong absorptions non-linear effects cannot always be neglected. This is especially the case for observation geometries, for which the light contributing to the measurement is crossing the atmosphere under spatially well-separated paths differing strongly in length and location, like in limb geometry. In these cases, often full retrieval algorithms are applied to address the non-linearities, requiring iterative forward modelling of absorption spectra involving time-consuming wavelength-by-wavelength radiative transfer modelling. In this study, we propose to describe the non-linear effects by additional sensitivity parameters that can be used e.g. to build up a lookup table. Together with widely used box air mass factors (effective light paths) describing the linear response to the increase in the trace gas amount, the higher-order sensitivity parameters eliminate the need for repeating the radiative transfer modelling when modifying the absorption scenario even in the presence of a strong absorption background. While the higher-order absorption structures can be described as separate fit parameters in the spectral analysis (so-called DOAS fit), in practice their quantitative evaluation requires good measurement quality (typically better than that available from current measurements). Therefore, we introduce an iterative retrieval algorithm correcting for the higher-order absorption structures not yet considered in the DOAS fit as well as the absorption dependence on
Non-linear models: applications in economics
Albu, Lucian-Liviu
2006-01-01
The study concentrated on demonstrating how non-linear modelling can be useful to investigate the behavioural of dynamic economic systems. Using some adequate non-linear models could be a good way to find more refined solutions to actually unsolved problems or ambiguities in economics. Beginning with a short presentation of the simplest non-linear models, then we are demonstrating how the dynamics of complex systems, as the economic system is, could be explained on the base of some more advan...
Composite Linear Models | Division of Cancer Prevention
By Stuart G. Baker The composite linear models software is a matrix approach to compute maximum likelihood estimates and asymptotic standard errors for models for incomplete multinomial data. It implements the method described in Baker SG. Composite linear models for incomplete multinomial data. Statistics in Medicine 1994;13:609-622. The software includes a library of thirty examples from the literature. |
Core seismic behaviour: linear and non-linear models
The usual methodology for the core seismic behaviour analysis leads to a double complementary approach: to define a core model to be included in the reactor-block seismic response analysis, simple enough but representative of basic movements (diagrid or slab), to define a finer core model, with basic data issued from the first model. This paper presents the history of the different models of both kinds. The inert mass model (IMM) yielded a first rough diagrid movement. The direct linear model (DLM), without shocks and with sodium as an added mass, let to two different ones: DLM 1 with independent movements of the fuel and radial blanket subassemblies, and DLM 2 with a core combined movement. The non-linear (NLM) ''CORALIE'' uses the same basic modelization (Finite Element Beams) but accounts for shocks. It studies the response of a diameter on flats and takes into account the fluid coupling and the wrapper tube flexibility at the pad level. Damping consists of one modal part of 2% and one part due to shocks. Finally, ''CORALIE'' yields the time-history of the displacements and efforts on the supports, but damping (probably greater than 2%) and fluid-structures interaction are still to be precised. The validation experiments were performed on a RAPSODIE core mock-up on scale 1, in similitude of 1/3 as to SPX 1. The equivalent linear model (ELM) was developed for the SPX 1 reactor-block response analysis and a specified seismic level (SB or SM). It is composed of several oscillators fixed to the diagrid and yields the same maximum displacements and efforts than the NLM. The SPX 1 core seismic analysis with a diagrid input spectrum which corresponds to a 0,1 g group acceleration, has been carried out with these models: some aspects of these calculations are presented here
Bayes linear covariance matrix adjustment for multivariate dynamic linear models
Wilkinson, Darren J
2008-01-01
A methodology is developed for the adjustment of the covariance matrices underlying a multivariate constant time series dynamic linear model. The covariance matrices are embedded in a distribution-free inner-product space of matrix objects which facilitates such adjustment. This approach helps to make the analysis simple, tractable and robust. To illustrate the methods, a simple model is developed for a time series representing sales of certain brands of a product from a cash-and-carry depot. The covariance structure underlying the model is revised, and the benefits of this revision on first order inferences are then examined.
Linear cavity optical-feedback cavity-enhanced absorption spectroscopy with a quantum cascade laser.
Bergin, A G V; Hancock, G; Ritchie, G A D; Weidmann, D
2013-07-15
A cw distributed feedback quantum cascade laser (DFB-QCL) coupled to a two-mirror linear optical cavity has been used to successfully demonstrate optical-feedback cavity-enhanced absorption spectroscopy (OF-CEAS) at 5.5 μm. The noise-equivalent absorption coefficient, α(min), was 2.4×10(-8) cm(-1) for 1 s averaging, limited by etalon-fringing. The temporal stability of the instrument allows NO detection down to 5 ppb in 2 s. PMID:23939085
Radiolysis of linear model compounds of polyamide
Polyamide oligomers of epsilon-aminocaproic acid (ACA) were used as model compounds. Six oligomers with the number of mers, 2-7, designated as K2-K7 were synthesized. The ACA oligomers were irradiated with 60Co gamma rays in an atmosphere of nitrogen and in air in a dose range from 0 to 1300 kGy. The concentration of the CHO, NH2 and COOH groups formed and the yields of gaseous products, hydrogen and carbon monoxide, as well as the absorption of oxygen, were determined. The polycaprolactam PA6 in the form of unstabilized fibres was investigated for comparison. The number of CHO groups increases with the dose for all oligomers; this value is, in air, for K5-K7 three times, for K3-K4 six times, and for K2 nine times as large as in the atmosphere of nitrogen. The number of NH2 groups goes through a maximum with increasing dose; in air the maximum is smaller and occurs at lower doses. The number of COOH groups changes only slightly with the dose; in air the number of COOH groups increases for longer oligomers (K5-K7). The concentration of hydrogen increases linearly with the dose both in the atmosphere of nitrogen and in air. In the latter case the radiation yields Gsub((H2)) are lower. (author)
Recursive Linear Models of Dynamic Economies
Lars Peter Hansen; Sargent, Thomas J.
1990-01-01
This paper describes a class of dynamic stochastic linear quadratic equilibrium models. A model is specified by naming lists of matrices that determine preferences, technology, and the information structure. Aggregate equilibrium allocations and prices are computed by solving a social planning problem in the form of an optimal linear regulator. Heterogeneity among agents is permitted. Several examples are computed.
Actuarial statistics with generalized linear mixed models
K. Antonio; J. Beirlant
2007-01-01
Over the last decade the use of generalized linear models (GLMs) in actuarial statistics has received a lot of attention, starting from the actuarial illustrations in the standard text by McCullagh and Nelder [McCullagh, P., Nelder, J.A., 1989. Generalized linear models. In: Monographs on Statistics
Rasulov, R. Ya.; Rasulov, V. R.; Eshboltaev, I.
2016-05-01
An occurrence of the current of the shift linear photovoltaic effect under two-photon absorption of light in semiconductors without a center of symmetry with a complex band structure is theoretically analyzed. The contributions both from the simultaneous absorption of two photons and successive absorption of two single photons to the photocurrent are taken into account.
Photon emission within the linear sigma model
Wunderlich, F
2015-01-01
Soft-photon emission rates are calculated within the linear sigma model. The investigation is aimed at answering the question to which extent the emissivities map out the phase structure of this particular effective model of strongly interacting matter.
Absorption Cross-section and Decay Rate of Rotating Linear Dilaton Black Holes
Sakalli, I
2016-01-01
We analytically study the scalar perturbation of non-asymptotically flat (NAF) rotating linear dilaton black holes (RLDBHs) in 4-dimensions. We show that both radial and angular wave equations can be solved in terms of the hypergeometric functions. The exact greybody factor (GF), the absorption cross-section (ACS), and the decay rate (DR) for the massless scalar waves are computed for these black holes (BHs). The results obtained for ACS and DR are discussed through graphs.
Linear and nonlinear fractional Voigt models
Chidouh, Amar; Guezane-Lakoud, Assia; Bebbouchi, Rachid; Bouaricha, Amor; Torres, Delfim F. M.
2016-01-01
We consider fractional generalizations of the ordinary differential equation that governs the creep phenomenon. Precisely, two Caputo fractional Voigt models are considered: a rheological linear model and a nonlinear one. In the linear case, an explicit Volterra representation of the solution is found, involving the generalized Mittag-Leffler function in the kernel. For the nonlinear fractional Voigt model, an existence result is obtained through a fixed point theorem. A nonlinear example, il...
Correlations and Non-Linear Probability Models
Breen, Richard; Holm, Anders; Karlson, Kristian Bernt
2014-01-01
Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations between...... the dependent variable of the latent variable model and its predictor variables. We show how this correlation can be derived from the parameters of non-linear probability models, develop tests for the statistical significance of the derived correlation, and illustrate its usefulness in two applications. Under...... certain circumstances, which we explain, the derived correlation provides a way of overcoming the problems inherent in cross-sample comparisons of the parameters of non-linear probability models....
Rethinking the Lintnerian Linear Valuation Model
Shih-Cheng Lee; Jiun-Lin Chen; Shu-Chen Lu; Lei Xu
2014-01-01
This paper develops and tests a new valuation model. Callen and Morel (2000) apply the Lintner (1956) dividend model to the famous Ohlson (1995) valuation model and develop the Lintnerian linear accounting valuation model (henceforth, the CM model). However, Bauer and Bhattacharyya (2007) suggest that the Lintner dividend model does not fit firm dividend policy behaviour appropriately and decide to construct another dividend policy process. This study applies their dividend model to construct...
Linear mixed models for longitudinal data
Molenberghs, Geert
2000-01-01
This paperback edition is a reprint of the 2000 edition. This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Several variations to the conventional linear mixed model are discussed (a heterogeity model, conditional linear mixed models). This book will be of interest to applied statisticians and biomedical researchers in industry, public health organizations, contract research organizations, and academia. The book is explanatory rather than mathematically rigorous. Most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated. However, some other commerc...
Modelling Loudspeaker Non-Linearities
Agerkvist, Finn T.
2007-01-01
polynomial expansions are rather poor at this, whereas an inverse polynomial expansion or localized fitting functions such as the gaussian are better suited for modelling the Bl-factor and compliance. For the inductance the sigmoid function is shown to give very good results. Finally the time varying...... property of the suspension is studied and it demonstrated that significant part of the variation can be predicted from the dissipated power....
On Estimation of Partially Linear Transformation Models
Lu, Wenbin; Zhang, Hao Helen
2010-01-01
We study a general class of partially linear transformation models, which extend linear transformation models by incorporating nonlinear covariate effects in survival data analysis. A new martingale-based estimating equation approach, consisting of both global and kernel-weighted local estimation equations, is developed for estimating the parametric and nonparametric covariate effects in a unified manner. We show that with a proper choice of the kernel bandwidth parameter, one can obtain the ...
Linear causal modeling with structural equations
Mulaik, Stanley A
2009-01-01
Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal
Statistical Tests for Mixed Linear Models
Khuri, André I; Sinha, Bimal K
2011-01-01
An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for these models a
Piecewise linear car-following modeling
Farhi, Nadir
2011-01-01
We present a traffic model which extends the linear car-following model as well as the min-plus traffic model (a model based on the min-plus algebra). A discrete-time car-dynamics describing the traffic on a 1-lane road without passing is interpreted as a dynamic programming equation of a stochastic optimal control problem of a Markov chain. This variational formulation permits to characterize the stability of the car-dynamics and to calculte the stationary regimes when they exist. The model is based on a piecewise linear approximation of the fundamental traffic diagram.
Linear mixed models in sensometrics
Kuznetsova, Alexandra
Today’s companies and researchers gather large amounts of data of different kind. In consumer studies the objective is the collection of the data to better understand consumer acceptance of products. In such studies a number of persons (generally not trained) are selected in order to score products...... in terms of preferences. In sensory studies the aim is the collection of the data to better describe products and differences of the products according to a number of sensory attributes. Here trained persons, so-called assessors, score the products in terms of different characteristics such as smell...... papers and software tools facilitating the developed methodologies. The primary advantage of the ANOVA approach is that it gives confidence intervals and significance tests for the various effects including the background variables used in the model and consequently a fast and reliable assessment and...
Matrix Tricks for Linear Statistical Models
Puntanen, Simo; Styan, George PH
2011-01-01
In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple "tricks" which simplify and clarify the treatment of a problem - both for the student and
Some new progress on the light absorption properties of linear alkyl benzene solvent
Yu, Guang-You; Huang, Ai-Zhong; Yu, Lei; Loh, Chang-Wei; Wang, Wen-Wen; Qian, Zhi-Qiang; Yang, Hai-Bo; Huang, Huang; Xu, Zong-Qiang; Zhu, Xue-Yuan; Xu, Bin; Qi, Ming
2015-01-01
Linear alkyl benzene (LAB) will be used as the solvent of a liquid scintillator mixture for the JUNO antineutrino experiment in the near future. Its light absorption property should therefore be understood prior to its effective use in the experiment. Attenuation length measurements at a light wavelength of 430 nm have been performed on samples of LAB prepared for the purpose of the JUNO experiment. Inorganic impurities in LAB have also been studied for their possibilities of light absorption in our wavelength of interest. In view of a tentative plan by the JUNO collaboration to utilize neutron capture with hydrogen in the detector, we have also presented in this work, a study on the carbon-hydrogen ratio and the relationship thereof with the attenuation length of the samples.
MODELING DATA INTEGRITY UNDER STOCHASTIC LINEAR CONSTRAINTS
Lee-Pin Shing
2015-06-01
Full Text Available The most commonly used data integrity models today are Bibba, Wilson-Clark and Chinese models. These models are designed for both data integrity protection and confidentiality. Many optimization problems are related to linear programming. In practice, these variables involved are probabilistic. This paper proposes a data integrity model based on data anomalies assuming data are under stochastic linear constraints. An algorithm is constructed using the simplex method to find confidence intervals for the problem solutions. In the end the results from Monte Carlo simulation are compared with those from simplex method.
Identification and Modelling of Linear Dynamic Systems
Stanislav Kocur
2006-01-01
Full Text Available System identification and modelling are very important parts of system control theory. System control is only as good as good is created model of system. So this article deals with identification and modelling problems. There are simple classification and evolution of identification methods, and then the modelling problem is described. Rest of paper is devoted to two most known and used models of linear dynamic systems.
Sjögren, Erik; Thörn, Helena; Tannergren, Christer
2016-06-01
Gastrointestinal (GI) drug absorption is a complex process determined by formulation, physicochemical and biopharmaceutical factors, and GI physiology. Physiologically based in silico absorption models have emerged as a widely used and promising supplement to traditional in vitro assays and preclinical in vivo studies. However, there remains a lack of comparative studies between different models. The aim of this study was to explore the strengths and limitations of the in silico absorption models Simcyp 13.1, GastroPlus 8.0, and GI-Sim 4.1, with respect to their performance in predicting human intestinal drug absorption. This was achieved by adopting an a priori modeling approach and using well-defined input data for 12 drugs associated with incomplete GI absorption and related challenges in predicting the extent of absorption. This approach better mimics the real situation during formulation development where predictive in silico models would be beneficial. Plasma concentration-time profiles for 44 oral drug administrations were calculated by convolution of model-predicted absorption-time profiles and reported pharmacokinetic parameters. Model performance was evaluated by comparing the predicted plasma concentration-time profiles, Cmax, tmax, and exposure (AUC) with observations from clinical studies. The overall prediction accuracies for AUC, given as the absolute average fold error (AAFE) values, were 2.2, 1.6, and 1.3 for Simcyp, GastroPlus, and GI-Sim, respectively. The corresponding AAFE values for Cmax were 2.2, 1.6, and 1.3, respectively, and those for tmax were 1.7, 1.5, and 1.4, respectively. Simcyp was associated with underprediction of AUC and Cmax; the accuracy decreased with decreasing predicted fabs. A tendency for underprediction was also observed for GastroPlus, but there was no correlation with predicted fabs. There were no obvious trends for over- or underprediction for GI-Sim. The models performed similarly in capturing dependencies on dose and
On Estimation of Partially Linear Transformation Models.
Lu, Wenbin; Zhang, Hao Helen
2010-06-01
We study a general class of partially linear transformation models, which extend linear transformation models by incorporating nonlinear covariate effects in survival data analysis. A new martingale-based estimating equation approach, consisting of both global and kernel-weighted local estimation equations, is developed for estimating the parametric and nonparametric covariate effects in a unified manner. We show that with a proper choice of the kernel bandwidth parameter, one can obtain the consistent and asymptotically normal parameter estimates for the linear effects. Asymptotic properties of the estimated nonlinear effects are established as well. We further suggest a simple resampling method to estimate the asymptotic variance of the linear estimates and show its effectiveness. To facilitate the implementation of the new procedure, an iterative algorithm is developed. Numerical examples are given to illustrate the finite-sample performance of the procedure. PMID:20802823
Strong absorption model and its associated potential
Using the example of 12C-208Pb elastic scattering at Elab=1449 MeV it is shown that, at sufficiently high energies, a full quantum mechanical inversion of heavy-ion scattering data can be performed. Furthermore it is pointed out that the strong absorption model as parametrized by McIntyre, Wang, and Becker is associated with a potential having strong repulsion at the origin. That repulsion is a remnant of the built-in point Coulomb S matrix. Finally, a systematic study is presented to define the necessary accuracy of experiment required to extend the knowledge of the nucleus-nucleus interaction to smaller radii
Non-linear finite element modeling
Mikkelsen, Lars Pilgaard
The note is written for courses in "Non-linear finite element method". The note has been used by the author teaching non-linear finite element modeling at Civil Engineering at Aalborg University, Computational Mechanics at Aalborg University Esbjerg, Structural Engineering at the University of the...... Southern Denmark and in Medicine and Technology at the Technical University of Denmark. The note focus on the applicability to actually code routines with the purpose to analyze a geometrically or material non-linear problem. The note is tried to be kept on so brief a form as possible, with the main focus...
Disc instantons in linear sigma models
We construct a linear sigma model for open-strings ending on special Lagrangian cycles of a Calabi-Yau manifold. We illustrate the construction for the cases considered by Aganagic and Vafa (AV). This leads naturally to concrete models for the moduli space of open-string instantons. These instanton moduli spaces can be seen to be intimately related to certain auxiliary boundary toric varieties. By considering the relevant Gelfand-Kapranov-Zelevinsky (GKZ) differential equations of the boundary toric variety, we obtain the contributions to the world volume superpotential on the A-branes from open-string instantons. By using an ansatz due to Aganagic, Klemm and Vafa (AKV), we obtain the relevant change of variables from the linear sigma model to the non-linear sigma model variables--the open-string mirror map. Using this mirror map, we obtain results in agreement with those of AV and AKV for the counting of holomorphic disc instantons
Rasulov, R. Ya.; Rasulov, V. R.; Eshboltaev, I.
2016-07-01
The ballistic contribution to the current of linear photovoltaic effect under two-photon absorption of light is calculated and theoretically analyzed for the semiconductors of a tetrahedral symmetry with a complex band structure consisting of two closely spaced subbands. The transitions between the branches of one band in cases of the simultaneous absorption of two photons and successive absorption of two single photons are taken into account.
Burgh, Eric B.; McCandliss, Stephan R.; Andersson, B-G; Feldman, Paul D.
2000-01-01
A sample of 59 sight lines to reddened Galactic OB stars was examined for correlations of the strength of the CO Fourth Positive (A - X) absorption band system with the ultraviolet interstellar extinction curve parameters. We used archival high-dispersion NEWSIPS IUE spectra to measure the CO absorption for comparison to parametric fits of the extinction curves from the literature. A strong correlation with the non-linear far-UV curvature term was found with greater absorption, normalized to ...
Faraway, Julian J
2005-01-01
Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway''s critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies. Following in those footsteps, Extending the Linear Model with R surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author''s treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the data of real examples, providing all of the R commands necessary to reproduce the analyses. All of the ...
Introduction to general and generalized linear models
Madsen, Henrik
2010-01-01
IntroductionExamples of types of data Motivating examples A first view on the modelsThe Likelihood PrincipleIntroduction Point estimation theory The likelihood function The score function The information matrix Alternative parameterizations of the likelihood The maximum likelihood estimate (MLE) Distribution of the ML estimator Generalized loss-function and deviance Quadratic approximation of the log-likelihood Likelihood ratio tests Successive testing in hypothesis chains Dealing with nuisance parameters General Linear ModelsIntroduction The multivariate normal distribution General linear mod
An R companion to linear statistical models
Hay-Jahans, Christopher
2011-01-01
Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: those who are familiar with the theory and applications of linear statistical models and wish to learn or enhance their skills in R; and those who are enrolled in an R-based course on regression and analysis of variance. For those who have never used R, the book begins with a self-contained introduction to R that lays the foundation for later chapters.This book includes extensive and carefully explained examples of how to write programs using the R programming language. These examples cove
Approximately exact calculations for linear mixed models
Lavine, Michael; Bray, Andrew; Hodges, Jim
2015-01-01
This paper is about computations for linear mixed models having two variances, $\\sigma^{2}_{e}$ for residuals and $\\sigma^{2}_{s}$ for random effects, though the ideas can be extended to some linear mixed models having more variances. Researchers are often interested in either the restricted (residual) likelihood $\\text{RL}(\\sigma_{e}^{2},\\sigma_{s}^{2})$ or the joint posterior $\\pi(\\sigma_{e}^{2},\\sigma_{s}^{2}\\,|\\,y)$ or their logarithms. Both $\\log\\text{RL}$ and $\\log\\pi$ can be multimodal...
Dynamic modeling under linear-exponential loss
Stanislav Anatolyev
2006-01-01
We develop a methodology of parametric modeling of time series dynamics when the underlying loss function is linear-exponential (Linex). We propose to directly model the dynamics of the conditional expectation that determines the optimal predictor. The procedure hinges on the exponential quasi maximum likelihood interpretation of the Linex loss and nicely fits the multiple error modeling framework. Many conclusions relating to estimation, inference and forecasting follow from results already ...
Ruin Probability in Linear Time Series Model
ZHANG Lihong
2005-01-01
This paper analyzes a continuous time risk model with a linear model used to model the claim process. The time is discretized stochastically using the times when claims occur, using Doob's stopping time theorem and martingale inequalities to obtain expressions for the ruin probability as well as both exponential and non-exponential upper bounds for the ruin probability for an infinite time horizon. Numerical results are included to illustrate the accuracy of the non-exponential bound.
Detailed Decompositions in Generalized Linear Models
Kaiser, Boris
2013-01-01
We propose a new approach for performing detailed decompositions of average outcome differentials, which can be applied to all types of generalized linear models. A simulation exercise demonstrates that our method produces more convincing results than existing methods. An empirical application to the immigrant-native wage differential in Switzerland is presented.
Non-linear Loudspeaker Unit Modelling
Pedersen, Bo Rohde; Agerkvist, Finn
2008-01-01
Simulations of a 6½-inch loudspeaker unit are performed and compared with a displacement measurement. The non-linear loudspeaker model is based on the major nonlinear functions and expanded with time-varying suspension behaviour and flux modulation. The results are presented with FFT plots of three...
Managing Clustered Data Using Hierarchical Linear Modeling
Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.
2012-01-01
Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…
Linear Parametric Model Checking of Timed Automata
Hune, Tohmas Seidelin; Romijn, Judi; Stoelinga, Mariëlle; Vaandrager, Frits W.
We present an extension of the model checker Uppaal capable of synthesize linear parameter constraints for the correctness of parametric timed automata. The symbolic representation of the (parametric) state-space is shown to be correct. A second contribution of this paper is the identication of a...
Sahin, Rubina; Tapadia, Kavita
2015-01-01
The three widely used isotherms Langmuir, Freundlich and Temkin were examined in an experiment using fluoride (F⁻) ion adsorption on a geo-material (limonite) at four different temperatures by linear and non-linear models. Comparison of linear and non-linear regression models were given in selecting the optimum isotherm for the experimental results. The coefficient of determination, r², was used to select the best theoretical isotherm. The four Langmuir linear equations (1, 2, 3, and 4) are discussed. Langmuir isotherm parameters obtained from the four Langmuir linear equations using the linear model differed but they were the same when using the nonlinear model. Langmuir-2 isotherm is one of the linear forms, and it had the highest coefficient of determination (r² = 0.99) compared to the other Langmuir linear equations (1, 3 and 4) in linear form, whereas, for non-linear, Langmuir-4 fitted best among all the isotherms because it had the highest coefficient of determination (r² = 0.99). The results showed that the non-linear model may be a better way to obtain the parameters. In the present work, the thermodynamic parameters show that the absorption of fluoride onto limonite is both spontaneous (ΔG 0). Scanning electron microscope and X-ray diffraction images also confirm the adsorption of F⁻ ion onto limonite. The isotherm and kinetic study reveals that limonite can be used as an adsorbent for fluoride removal. In future we can develop new technology for fluoride removal in large scale by using limonite which is cost-effective, eco-friendly and is easily available in the study area. PMID:26676015
XIE Wen-Fang
2009-01-01
The linear and nonlinear optical properties of a hydrogenic donor in a disc-like parabolic quantum dot in the presence of an external magnetic field are studied. The calculations were performed within the effective mass approximation, using the matrix diagonalization method and the compact density-matrix approach. The linear and nonlinear optical absorption coefficients between the ground (L = 0) and the first excited state (L = 1) have been examined based on the computed energies and wave functions. We find that the linear, nonlinear third-order, and total optical absorption coefficients are strongly affected by the confinement strength of QDs, the external magnetic field, and the incident optical intensity.
On Bayes linear unbiased estimation of estimable functions for the singular linear model
ZHANG Weiping; WEI Laisheng
2005-01-01
The unique Bayes linear unbiased estimator (Bayes LUE) of estimable functions is derived for the singular linear model. The superiority of Bayes LUE over ordinary best linear unbiased estimator is investigated under mean square error matrix (MSEM)criterion.
Strong absorption model analysis of alpha scattering
Angular distribution of alpha-particles at several energies, Eα = 21 ∼ 85.6 MeV from a number of nuclei between 20Ni and 119Sn, extending to wide angular range up to ∼ 160 deg. C in some cases, have been analyzed in terms of three-parameter strong absorption model of Frahn and Venter. Interaction radius and surface diffuseness are obtained from the parameter values rendering the best fit to the elastic scattering data. The inelastic scattering of alpha-particles from a number of nuclei, leading to quadrupole and octupole excitations has also been studied giving the deformation parameters βL. (author). 14 refs, 7 figs, 3 tabs
Multiple Imputations for LInear Regression Models
Brownstone, David
1991-01-01
Rubin (1987) has proposed multiple imputations as a general method for estimation in the presence of missing data. Rubinâ€™s results only strictly apply to Bayesian models, but Schenker and Welsh (1988) directly prove the consistency Â multiple imputations inference~ when there are missing values of the dependent variable in linear regression models. This paper extends and modifies Schenker and Welshâ€™s theorems to give conditions where multiple imputations yield consistent inferences for bo...
Linear Model Predictive Control of Induction Machine
Mynář, Z.
2015-01-01
This article presents new control algorithm for induction machine based on linear model predictive control (MPC). Controller works in similar manners as field oriented control (FOC), but control is performed in stator coordinates. This reduces computational demands as Park’s transformation is absent and induction machine mathematical model in stator coordinates contains less nonlinear elements. Another aim of proposed controller was to achieve fast torque response.
Cosmological models with linearly varying deceleration parameter
Akarsu, Özgür; Dereli, Tekin; Oflaz, Neslihan
2011-01-01
arXiv:1102.0915v3 [gr-qc] 8 Sep 2011 Cosmological models with linearly varying deceleration parameter ¨O zg¨ur Akarsu Tekin Dereli † Department of Physics, Ko¸c University, 34450 ˙Istanbul/Turkey. Abstract We propose a new law for the deceleration parameter that varies linearly with time and covers Berman’s law where it is constant. Our law not only allows one to generalize many exact solutions that were obtained assuming constant deceleration parameter, but al...
Off-resonance energy absorption in a linear Paul trap due to mass selective resonant quenching
Sivarajah, I; Wells, J E; Narducci, F A; Smith, W W
2013-01-01
Linear Paul r.f. ion traps (LPT) are used in many experimental studies such as mass spectrometry, atom-ion collisions and ion-molecule reactions. Mass selective resonant quenching (MSRQ) is implemented in LPT either to identify a charged particle's mass or to remove unwanted ions from a controlled experimental environment. In the latter case, MSRQ can introduce undesired heating to co-trapped ions of different mass, whose secular motion is off resonance with the quenching ac field, which we call off-resonance energy absorption (OREA). We present simulations and experimental evidence that show that the OREA increases exponentially with the number of ions loaded into the trap and with the amplitude of the off-resonance external ac field.
Testing Parametric versus Semiparametric Modelling in Generalized Linear Models
Härdle, W.K.; Mammen, E.; Müller, M.D.
1996-01-01
We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known function, b is an unknown parameter vector, and m is an unknown function.The paper introduces a test statistic which allows to decide between a parametric and a semiparametric model: (i) m is linear, i.e. m(
Ceymann, Harald; Rosspeintner, Arnulf; Schreck, Maximilian H; Mützel, Carina; Stoy, Andreas; Vauthey, Eric; Lambert, Christoph
2016-06-28
The linear and nonlinear optical properties of a series of oligomeric squaraine dyes were investigated by one-photon absorption spectroscopy (1PA) and two-photon absorption (2PA) induced fluorescence spectroscopy. The superchromophores are based on two indolenine squaraine dyes with transoid (SQA) and cisoid configuration (SQB). Using these monomers, linear dimers and trimers as well as star-shaped trimers and hexamers with benzene or triphenylamine cores were synthesised and investigated. The red-shifted and intensified 1PA spectra of all superchromophores could well be explained by exciton coupling theory. In the linear chromophore arrangements we also found superradiance of fluorescence but not in the branched systems. Furthermore, the 2PA showed enhanced cross sections for the linear oligomers but only additivity for the branched systems. This emphasizes that the enhancement of the 2PA cross section in the linear arrangements is probably caused by orbital interactions of higher excited configurations. PMID:27264847
Absorptive Capacity of Information Technology and Its Conceptual Model
BI Xinhua; YU Cuiling
2008-01-01
In order to examine the problem of how to improve the use of information technology (IT) in enterprises, this paper makes an exploration from the perspective of organizational absorptive capacity. We propose the concept of IT absorptive capacity from an organizational level. A dynamic process model is developed to further analyze IT absorption. IT absorptive capacity of this process is embodied as six forms: identification, adoption, adaptation, acceptance, infusion, and knowledge management. By means of questionnaire surveys of 76 Chinese enterprises, the main factors that favor or disable the capacity of each stage are discovered. Using the method of system dynamics, a conceptual model of IT absorptive capacity is developed to analyze the action mechanism of the factors in detail. The model indicates that the critical factors are embodied in the aspect of management. Furthermore, it demonstrates that IT absorption is a spiral process, during which IT absorptive capacity evolves dynamically and, consequently, promotes IT use.
Moisan, John R.; Moisan, Tiffany A. H.; Linkswiler, Matthew A.
2011-01-01
Phytoplankton absorption spectra and High-Performance Liquid Chromatography (HPLC) pigment observations from the Eastern U.S. and global observations from NASA's SeaBASS archive are used in a linear inverse calculation to extract pigment-specific absorption spectra. Using these pigment-specific absorption spectra to reconstruct the phytoplankton absorption spectra results in high correlations at all visible wavelengths (r(sup 2) from 0.83 to 0.98), and linear regressions (slopes ranging from 0.8 to 1.1). Higher correlations (r(sup 2) from 0.75 to 1.00) are obtained in the visible portion of the spectra when the total phytoplankton absorption spectra are unpackaged by multiplying the entire spectra by a factor that sets the total absorption at 675 nm to that expected from absorption spectra reconstruction using measured pigment concentrations and laboratory-derived pigment-specific absorption spectra. The derived pigment-specific absorption spectra were further used with the total phytoplankton absorption spectra in a second linear inverse calculation to estimate the various phytoplankton HPLC pigments. A comparison between the estimated and measured pigment concentrations for the 18 pigment fields showed good correlations (r(sup 2) greater than 0.5) for 7 pigments and very good correlations (r(sup 2) greater than 0.7) for chlorophyll a and fucoxanthin. Higher correlations result when the analysis is carried out at more local geographic scales. The ability to estimate phytoplankton pigments using pigment-specific absorption spectra is critical for using hyperspectral inverse models to retrieve phytoplankton pigment concentrations and other Inherent Optical Properties (IOPs) from passive remote sensing observations.
Improved testing inference in mixed linear models
Melo, Tatiane F N; Cribari-Neto, Francisco; 10.1016/j.csda.2008.12.007
2011-01-01
Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Oftentimes, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test and also to a test obtained from a modified profile likelihood function. Our results generalize those in Zucker et al. (Journal of the Royal Statistical Society B, 2000, 62, 827-838) by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report numerical evidence which shows that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presente...
Linear transport models for adsorbing solutes
Roth, K.; Jury, W. A.
1993-04-01
A unified linear theory for the transport of adsorbing solutes through soils is presented and applied to analyze movement of napropamide through undisturbed soil columns. The transport characteristics of the soil are expressed in terms of the travel time distribution of the mobile phase which is then used to incorporate local interaction processes. This approach permits the analysis of all linear transport processes, not only the small subset for which a differential description is known. From a practical point of view, it allows the direct use of measured concentrations or fluxes of conservative solutes to characterize the mobile phase without first subjecting them to any model. For complicated flow regimes, this may vastly improve the identification of models and estimation of their parameters for the local adsorption processes.
Nonlinear damping and quasi-linear modelling.
Elliott, S J; Ghandchi Tehrani, M; Langley, R S
2015-09-28
The mechanism of energy dissipation in mechanical systems is often nonlinear. Even though there may be other forms of nonlinearity in the dynamics, nonlinear damping is the dominant source of nonlinearity in a number of practical systems. The analysis of such systems is simplified by the fact that they show no jump or bifurcation behaviour, and indeed can often be well represented by an equivalent linear system, whose damping parameters depend on the form and amplitude of the excitation, in a 'quasi-linear' model. The diverse sources of nonlinear damping are first reviewed in this paper, before some example systems are analysed, initially for sinusoidal and then for random excitation. For simplicity, it is assumed that the system is stable and that the nonlinear damping force depends on the nth power of the velocity. For sinusoidal excitation, it is shown that the response is often also almost sinusoidal, and methods for calculating the amplitude are described based on the harmonic balance method, which is closely related to the describing function method used in control engineering. For random excitation, several methods of analysis are shown to be equivalent. In general, iterative methods need to be used to calculate the equivalent linear damper, since its value depends on the system's response, which itself depends on the value of the equivalent linear damper. The power dissipation of the equivalent linear damper, for both sinusoidal and random cases, matches that dissipated by the nonlinear damper, providing both a firm theoretical basis for this modelling approach and clear physical insight. Finally, practical examples of nonlinear damping are discussed: in microspeakers, vibration isolation, energy harvesting and the mechanical response of the cochlea. PMID:26303921
Decomposed Implicit Models of Piecewise - Linear Networks
J. Brzobohaty
1992-05-01
Full Text Available The general matrix form of the implicit description of a piecewise-linear (PWL network and the symbolic block diagram of the corresponding circuit model are proposed. Their decomposed forms enable us to determine quite separately the existence of the individual breakpoints of the resultant PWL characteristic and their coordinates using independent network parameters. For the two-diode and three-diode cases all the attainable types of the PWL characteristic are introduced.
Data perturbation analysis of a linear model
无
2000-01-01
The linear model features were carefully studied in the cases of data perturbation and mean shift perturbation.Some important features were also proved mathematically. The results show that the mean shift perturbation is equivalentto the data perturbation, that is, adding a parameter to an observation equation means that this set of data is deleted fromthe data set. The estimate of this parameter is its predicted residual in fact
From spiking neuron models to linear-nonlinear models.
Srdjan Ostojic
Full Text Available Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF, exponential integrate-and-fire (EIF and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.
Burgh, E B; Andersson, B G; Feldman, P D; Burgh, Eric B.; Candliss, Stephan R. Mc; Feldman, Paul D.
2000-01-01
A sample of 59 sight lines to reddened Galactic OB stars was examined for correlations of the strength of the CO Fourth Positive (A - X) absorption band system with the ultraviolet interstellar extinction curve parameters. We used archival high-dispersion NEWSIPS IUE spectra to measure the CO absorption for comparison to parametric fits of the extinction curves from the literature. A strong correlation with the non-linear far-UV curvature term was found with greater absorption, normalized to E(B-V), being associated with more curvature. A weaker trend with the linear extinction term was also found. Mechanisms for enhancing CO in dust environments exhibiting high non-linear curvature are discussed.
The analytical expressions of linear and nonlinear optical absorption coefficients and refractive index changes in a quantum dot with a hydrogenic impurity are obtained by using the compact-density-matrix approach and iterative method. The wave functions and the energy levels are obtained by using the variational method. Numerical results show that the optical absorption coefficients and refractive index changes are strongly affected by the hydrogenic impurity. (paper)
In modeling dense and partially ionized matter, the treatment of the free electrons remains an important issue. Compared to bound electrons, the delocalized and non-discrete nature of these electrons is responsible to treat them differently, which is usually adopted in the modeling of radiative properties of plasmas. However, in order to avoid inconsistencies in the calculation of absorption spectra, all the electrons should be described in the same formalism. We use two variational average-atom models: a semi-classical and a quantum model, which allow this common treatment for all the electrons. We calculate the photo-extinction cross-section, by applying the framework of the linear dynamical response theory to each of these models of an atom in a plasma. For this study, we develop and use a self-consistent approach, of random-phase-approximation (RPA) type, which, while going beyond the independent electron response, permits to evaluate the collective effects by the introduction of the dynamical polarization. This approach uses the formalism of the time dependent density functional theory (TDDFT), applied in the case of an atomic system immersed in a plasma. For both models, semi-classical and quantum, we derive and verify in our calculations, a new sum rule, which allows the evaluation of the atomic dipole from a finite volume in the plasma. This sum rule turns out to be a crucial device in the calculation of radiative properties of atoms in dense plasmas. (author)
Stochastic linear programming models, theory, and computation
Kall, Peter
2011-01-01
This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup. To facilitate use as a text, exercises are included throughout the book, and web access is provided to a student version of the authors’ SLP-IOR software. Additionally, the authors have updated the Guide to Available Software, and they have included newer algorithms and modeling systems for SLP. The book is thus suitable as a text for advanced courses in stochastic optimization, and as a reference to the field. From Reviews of the First Edition: "The book presents a comprehensive study of stochastic linear optimization problems and their applications. … T...
Neural Network for Combining Linear and Non-Linear Modelling of Dynamic Systems
Madsen, Per Printz
1994-01-01
The purpose of this paper is to develop a method to combine linear models with MLP networks. In other words to find a method to make a non-linear and multivariable model that performs at least as good as a linear model, when the training data lacks information....
Bayesian Discovery of Linear Acyclic Causal Models
Hoyer, Patrik O
2012-01-01
Methods for automated discovery of causal relationships from non-interventional data have received much attention recently. A widely used and well understood model family is given by linear acyclic causal models (recursive structural equation models). For Gaussian data both constraint-based methods (Spirtes et al., 1993; Pearl, 2000) (which output a single equivalence class) and Bayesian score-based methods (Geiger and Heckerman, 1994) (which assign relative scores to the equivalence classes) are available. On the contrary, all current methods able to utilize non-Gaussianity in the data (Shimizu et al., 2006; Hoyer et al., 2008) always return only a single graph or a single equivalence class, and so are fundamentally unable to express the degree of certainty attached to that output. In this paper we develop a Bayesian score-based approach able to take advantage of non-Gaussianity when estimating linear acyclic causal models, and we empirically demonstrate that, at least on very modest size networks, its accur...
The Key Solution Algorithm of Linear Programming Model
Liu Jun; Zhao Chuan Cheng; Ren Zhi Guo; Feng Zhong Yi; Zhu Zheng Ping
2016-01-01
Linear programming problem is a common problem, and to solve the linear model is more plagued. The paper generating algorithm is based on mathematical theory and composition. The design of feasible solution algorithm illustrates key linear programming model, then we can find a better way to solve the linear programming model solutions.
A novel parameterization of x-ray interaction cross-sections is developed, and employed to describe the x-ray linear attenuation coefficient and mass energy absorption coefficient for both elements and mixtures. The new parameterization scheme addresses the Z-dependence of elemental cross-sections (per electron) using a simple function of atomic number, Z. This obviates the need for a complicated mathematical formalism. Energy dependent coefficients describe the Z-direction curvature of the cross-sections. The composition dependent quantities are the electron density and statistical moments describing the elemental distribution. We show that it is possible to describe elemental cross-sections for the entire periodic table and at energies above the K-edge (from 6 keV to 125 MeV), with an accuracy of better than 2% using a parameterization containing not more than five coefficients. For the biologically important elements and the energy range 30- keV, the parameterization utilizes four coefficients. At higher energies, the parameterization uses fewer coefficients with only two coefficients needed at megavoltage energies
Continuum Eigenmodes in Some Linear Stellar Models
Winfield, Christopher J
2016-01-01
We apply parallel approaches in the study of continuous spectra to adiabatic stellar models. We seek continuum eigenmodes for the LAWE formulated as both finite difference and linear differential equations. In particular, we apply methods of Jacobi matrices and methods of subordinancy theory in these respective formulations. We find certain pressure-density conditions which admit positive-measured sets of continuous oscillation spectra under plausible conditions on density and pressure. We arrive at results of unbounded oscillations and computational or, perhaps, dynamic instability.
Sparse Linear Modeling of Speech from EEG
Tiger, Mattias
2014-01-01
For people with hearing impairments, attending to a single speaker in a multi-talker background can be very difficult and something which the current hearing aids can barely help with. Recent studies have shown that the audio stream a human focuses on can be found among the surrounding audio streams, using EEG and linear models. With this rises the possibility of using EEG to unconsciously control future hearing aids such that the attuned sounds get enhanced, while the rest are damped. For su...
The Piecewise Linear Reactive Flow Rate Model
Vitello, P; Souers, P C
2005-07-22
Conclusions are: (1) Early calibrations of the Piece Wise Linear reactive flow model have shown that it allows for very accurate agreement with data for a broad range of detonation wave strengths. (2) The ability to vary the rate at specific pressures has shown that corner turning involves competition between the strong wave that travels roughly in a straight line and growth at low pressure of a new wave that turns corners sharply. (3) The inclusion of a low pressure de-sensitization rate is essential to preserving the dead zone at large times as is observed.
F-theory and linear sigma models
Bershadsky, M; Greene, Brian R; Johansen, A; Lazaroiu, C I
1998-01-01
We present an explicit method for translating between the linear sigma model and the spectral cover description of SU(r) stable bundles over an elliptically fibered Calabi-Yau manifold. We use this to investigate the 4-dimensional duality between (0,2) heterotic and F-theory compactifications. We indirectly find that much interesting heterotic information must be contained in the `spectral bundle' and in its dual description as a gauge theory on multiple F-theory 7-branes. A by-product of these efforts is a method for analyzing semistability and the splitting type of vector bundles over an elliptic curve given as the sheaf cohomology of a monad.
Linear Stochastic Models of Nonlinear Dynamical Systems
Eyink, G L
1998-01-01
We investigate in this work the validity of linear stochastic models for nonlinear dynamical systems. We exploit as our basic tool a previously proposed Rayleigh-Ritz approximation for the effective action of nonlinear dynamical systems started from random initial conditions. The present paper discusses only the case where the PDF-Ansatz employed in the variational calculation is ``Markovian'', i.e. is determined completely by the present values of the moment-averages. In this case we show that the Rayleigh-Ritz effective action of the complete set of moment-functions that are employed in the closure has a quadratic part which is always formally an Onsager-Machlup action. Thus, subject to satisfaction of the requisite realizability conditions on the noise covariance, a linear Langevin model will exist which reproduces exactly the joint 2-time correlations of the moment-functions. We compare our method with the closely related formalism of principal oscillation patterns (POP), which, in the approach of C. Penl...
Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus
Jelonek, M
2006-01-01
The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of modeling hierarchical linear equations and estimation based on MPlus software. I present my own model to illustrate the impact of different factors on school acceptation level.
Modeling patterns in data using linear and related models
This report considers the use of linear models for analyzing data related to reliability and safety issues of the type usually associated with nuclear power plants. The report discusses some of the general results of linear regression analysis, such as the model assumptions and properties of the estimators of the parameters. The results are motivated with examples of operational data. Results about the important case of a linear regression model with one covariate are covered in detail. This case includes analysis of time trends. The analysis is applied with two different sets of time trend data. Diagnostic procedures and tests for the adequacy of the model are discussed. Some related methods such as weighted regression and nonlinear models are also considered. A discussion of the general linear model is also included. Appendix A gives some basic SAS programs and outputs for some of the analyses discussed in the body of the report. Appendix B is a review of some of the matrix theoretic results which are useful in the development of linear models
Modeling water/lithium bromide absorption chillers in ASPEN Plus
Highlights: → Single- and double-effect water/lithium bromide absorption chiller designs are numerically modeled using ASPEN. → The modeling procedure is described and the results are compared to published modeling data to access prediction accuracy. → Predictions for the single- and double-effect designs are within 3% and 5%, respectively of published data for all cycle parameters of interest. → The absorption cycle models presented allow investigation of using absorption chillers for waste heat utilization in the oil and gas industry. -- Abstract: Absorption chillers are a viable option for providing waste heat-powered cooling or refrigeration in oil and gas processing plants, thereby improving energy efficiency. In this paper, single- and double-effect water/lithium bromide absorption chiller designs are numerically modeled using ASPEN. The modeling procedure is described and the results are compared to published modeling data to access prediction accuracy. Predictions for the single- and double-effect designs are within 3% and 5%, respectively of published data for all cycle parameters of interest. The absorption cycle models presented not only allow investigation into the benefits of using absorption chillers for waste heat utilization in the oil and gas industry, but are also generically applicable to a wide range of other applications.
Linear models in the mathematics of uncertainty
Mordeson, John N; Clark, Terry D; Pham, Alex; Redmond, Michael A
2013-01-01
The purpose of this book is to present new mathematical techniques for modeling global issues. These mathematical techniques are used to determine linear equations between a dependent variable and one or more independent variables in cases where standard techniques such as linear regression are not suitable. In this book, we examine cases where the number of data points is small (effects of nuclear warfare), where the experiment is not repeatable (the breakup of the former Soviet Union), and where the data is derived from expert opinion (how conservative is a political party). In all these cases the data is difficult to measure and an assumption of randomness and/or statistical validity is questionable. We apply our methods to real world issues in international relations such as nuclear deterrence, smart power, and cooperative threat reduction. We next apply our methods to issues in comparative politics such as successful democratization, quality of life, economic freedom, political stability, and fail...
Interacting Dark Energy Models -- Scalar Linear Perturbations
Perico, E L D
2016-01-01
We extend the dark sector interacting models assuming the dark energy as the sum of independent contributions $\\rho_{\\Lambda} =\\sum_i\\rho_{\\Lambda i}$, associated with (and interacting with) each of the $i$ material species. We derive the linear scalar perturbations for two interacting dark energy scenarios, modeling its cosmic evolution and identifying their different imprints in the CMB and matter power spectrum. Our treatment was carried out for two phenomenological motivated expressions of the dark energy density, $\\rho_\\Lambda(H^2)$ and $\\rho_\\Lambda(R)$. The $\\rho_\\Lambda(H^2)$ description turned out to be a full interacting model, i.e., the dark energy interacts with everyone material species in the universe, whereas the $\\rho_\\Lambda(R)$ description only leads to interactions between dark energy and the non-relativistic matter components; which produces different imprints of the two models on the matter power spectrum. A comparison with the Planck 2015 data was made in order to constrain the free para...
Wan, Yuhang; Carlson, John A; Kesler, Benjamin A; Peng, Wang; Su, Patrick; Al-Mulla, Saoud A; Lim, Sung Jun; Smith, Andrew M; Dallesasse, John M; Cunningham, Brian T
2016-01-01
A compact analysis platform for detecting liquid absorption and emission spectra using a set of optical linear variable filters atop a CMOS image sensor is presented. The working spectral range of the analysis platform can be extended without a reduction in spectral resolution by utilizing multiple linear variable filters with different wavelength ranges on the same CMOS sensor. With optical setup reconfiguration, its capability to measure both absorption and fluorescence emission is demonstrated. Quantitative detection of fluorescence emission down to 0.28 nM for quantum dot dispersions and 32 ng/mL for near-infrared dyes has been demonstrated on a single platform over a wide spectral range, as well as an absorption-based water quality test, showing the versatility of the system across liquid solutions for different emission and absorption bands. Comparison with a commercially available portable spectrometer and an optical spectrum analyzer shows our system has an improved signal-to-noise ratio and acceptable spectral resolution for discrimination of emission spectra, and characterization of colored liquid's absorption characteristics generated by common biomolecular assays. This simple, compact, and versatile analysis platform demonstrates a path towards an integrated optical device that can be utilized for a wide variety of applications in point-of-use testing and point-of-care diagnostics. PMID:27389070
Wan, Yuhang; Carlson, John A.; Kesler, Benjamin A.; Peng, Wang; Su, Patrick; Al-Mulla, Saoud A.; Lim, Sung Jun; Smith, Andrew M.; Dallesasse, John M.; Cunningham, Brian T.
2016-01-01
A compact analysis platform for detecting liquid absorption and emission spectra using a set of optical linear variable filters atop a CMOS image sensor is presented. The working spectral range of the analysis platform can be extended without a reduction in spectral resolution by utilizing multiple linear variable filters with different wavelength ranges on the same CMOS sensor. With optical setup reconfiguration, its capability to measure both absorption and fluorescence emission is demonstrated. Quantitative detection of fluorescence emission down to 0.28 nM for quantum dot dispersions and 32 ng/mL for near-infrared dyes has been demonstrated on a single platform over a wide spectral range, as well as an absorption-based water quality test, showing the versatility of the system across liquid solutions for different emission and absorption bands. Comparison with a commercially available portable spectrometer and an optical spectrum analyzer shows our system has an improved signal-to-noise ratio and acceptable spectral resolution for discrimination of emission spectra, and characterization of colored liquid’s absorption characteristics generated by common biomolecular assays. This simple, compact, and versatile analysis platform demonstrates a path towards an integrated optical device that can be utilized for a wide variety of applications in point-of-use testing and point-of-care diagnostics. PMID:27389070
Numerical linearized MHD model of flapping oscillations
Korovinskiy, D. B.; Ivanov, I. B.; Semenov, V. S.; Erkaev, N. V.; Kiehas, S. A.
2016-06-01
Kink-like magnetotail flapping oscillations in a Harris-like current sheet with earthward growing normal magnetic field component Bz are studied by means of time-dependent 2D linearized MHD numerical simulations. The dispersion relation and two-dimensional eigenfunctions are obtained. The results are compared with analytical estimates of the double-gradient model, which are found to be reliable for configurations with small Bz up to values ˜ 0.05 of the lobe magnetic field. Coupled with previous results, present simulations confirm that the earthward/tailward growth direction of the Bz component acts as a switch between stable/unstable regimes of the flapping mode, while the mode dispersion curve is the same in both cases. It is confirmed that flapping oscillations may be triggered by a simple Gaussian initial perturbation of the Vz velocity.
Ming-xiang Cao; Fan-chao Kong
2009-01-01
By using the vector-method of matrix,we study Growth Curve Model with respect to linear constraint.Under matrix loss function and vector loss function,we obtain necessary and sufficient conditions for admissibility of linear estimators of parameters in the inhomogeneous linear class.
Self, B D; Moore, D S
1998-01-01
The DeVoe polarizability theory is used to calculate vibrational circular dichroism (VCD) and infrared (IR) absorption spectra of four polyribonucleotides: poly(rA) x poly(rU), poly(rU) x poly(rA) x poly(rU), poly(rG) x poly(rC), and poly(rC+) x poly(rI) x poly(rC). This is the first report on the use of the DeVoe theory to calculate VCD, oriented VCD, IR absorption, and IR linear dichroism (LD) spectra of double- and triple-stranded polyribonucleotides. Results are reported for DeVoe theory ...
Alskär, Oskar; Bagger, Jonatan I; Røge, Rikke M;
2015-01-01
and gastric emptying after tests with varying glucose doses. The developed model's performance was compared to empirical models. To develop our model, data from oral and intravenous glucose challenges in patients with type 2 diabetes and healthy control subjects were used together with present knowledge...... of small intestinal transit time, glucose inhibition of gastric emptying, and saturable absorption of glucose over the epithelium to improve the description of gastric emptying and glucose absorption in the IGI model. Duodenal glucose was found to inhibit gastric emptying. The performance of the saturable...... glucose absorption was superior to linear absorption regardless of the gastric emptying model applied. The semiphysiological model developed performed better than previously published empirical models and allows better understanding of the mechanisms underlying glucose absorption. In conclusion, our new...
Piecewise Linear-Linear Latent Growth Mixture Models with Unknown Knots
Kohli, Nidhi; Harring, Jeffrey R.; Hancock, Gregory R.
2013-01-01
Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear-linear latent growth mixture model (LGMM) for describing segmented change of…
Pascale KULISA; Cédric DANO
2006-01-01
Three linear two-equation turbulence models k- ε, k- ω and k- 1 and a non-linear k- l model are used for aerodynamic and thermal turbine flow prediction. The pressure profile in the wake and the heat transfer coefficient on the blade are compared with experimental data. Good agreement is obtained with the linear k- l model. No significant modifications are observed with the non-linear model. The balance of transport equation terms in the blade wake is also presented. Linear and non-linear k- l models are evaluated to predict the threedimensional vortices characterising the turbine flows. The simulations show that the passage vortex is the main origin of the losses.
Hierarchical linear regression models for conditional quantiles
TIAN; Maozai
2006-01-01
The quantile regression has several useful features and therefore is gradually developing into a comprehensive approach to the statistical analysis of linear and nonlinear response models,but it cannot deal effectively with the data with a hierarchical structure.In practice,the existence of such data hierarchies is neither accidental nor ignorable,it is a common phenomenon.To ignore this hierarchical data structure risks overlooking the importance of group effects,and may also render many of the traditional statistical analysis techniques used for studying data relationships invalid.On the other hand,the hierarchical models take a hierarchical data structure into account and have also many applications in statistics,ranging from overdispersion to constructing min-max estimators.However,the hierarchical models are virtually the mean regression,therefore,they cannot be used to characterize the entire conditional distribution of a dependent variable given high-dimensional covariates.Furthermore,the estimated coefficient vector (marginal effects)is sensitive to an outlier observation on the dependent variable.In this article,a new approach,which is based on the Gauss-Seidel iteration and taking a full advantage of the quantile regression and hierarchical models,is developed.On the theoretical front,we also consider the asymptotic properties of the new method,obtaining the simple conditions for an n1/2-convergence and an asymptotic normality.We also illustrate the use of the technique with the real educational data which is hierarchical and how the results can be explained.
Non linear behaviour of cell tensegrity models
Alippi, A.; Bettucci, A.; Biagioni, A.; Conclusio, D.; D'Orazio, A.; Germano, M.; Passeri, D.
2012-05-01
Tensegrity models for the cytoskeleton structure of living cells is largely used nowadays for interpreting the biochemical response of living tissues to mechanical stresses. Microtubules, microfilaments and filaments are the microscopic cell counterparts of struts (microtubules) and cables (microfilaments and filaments) in the macroscopic world: the formers oppose to compression, the latters to tension, thus yielding an overall structure, light and highly deformable. Specific cell surface receptors, such as integrins, act as the coupling elements that transmit the outside mechanical stress state into the cell body. Reversible finite deformations of tensegrity structures have been widely demonstrated experimentally and in a number of living cell simulations. In the present paper, the bistability behaviour of two general models, the linear bar oscillator and the icosahedron, is studied, as they are both obtained from mathematical simulation, the former, and from larger scale experiments, the latter. The discontinuity in the frequency response of the oscillation amplitude and the lateral bending of the resonance curves are put in evidence, as it grows larger as the driving amplitude increases, respectively.
Multiple Linear Regression Models in Outlier Detection
S.M.A.Khaleelur Rahman
2012-02-01
Full Text Available Identifying anomalous values in the real-world database is important both for improving the quality of original data and for reducing the impact of anomalous values in the process of knowledge discovery in databases. Such anomalous values give useful information to the data analyst in discovering useful patterns. Through isolation, these data may be separated and analyzed. The analysis of outliers and influential points is an important step of the regression diagnostics. In this paper, our aim is to detect the points which are very different from the others points. They do not seem to belong to a particular population and behave differently. If these influential points are to be removed it will lead to a different model. Distinction between these points is not always obvious and clear. Hence several indicators are used for identifying and analyzing outliers. Existing methods of outlier detection are based on manual inspection of graphically represented data. In this paper, we present a new approach in automating the process of detecting and isolating outliers. Impact of anomalous values on the dataset has been established by using two indicators DFFITS and Cook’sD. The process is based on modeling the human perception of exceptional values by using multiple linear regression analysis.
Atmospheric Absorption Models for the Millimeter Wave Range
Kuhn, Thomas
2003-01-01
This thesis deals with absorption models of water vapor, oxygen and nitrogen which are part of the Atmospheric Radiative Transfer System, ARTS, which is a joint development of the Department of Radio and Space Science, Chalmers University of Technology, Göteborg and the Institute of Environmental Physics, University of Bremen. ARTS is designed to be used in remotely sensed data analysis. Since the absorption models are embedded in the broader frame of the radiative transfer equation, the main...
Bao, J.; Lin, Z.; Kuley, A.; Wang, Z. X.
2016-06-01
Effects of toroidicity on linear mode conversion and absorption of lower hybrid (LH) waves in fusion plasmas have been studied using electromagnetic particle simulation. The simulation confirms that the toroidicity induces an upshift of parallel refractive index when LH waves propagate from the tokamak edge toward the core, which affects the radial position for the mode conversion between slow and fast LH waves. Furthermore, moving LH antenna launch position from low field side toward high field side leads to a larger upshift of the parallel refractive index, which helps the slow LH wave penetration into the tokamak core. The broadening of the poloidal spectrum of the wave-packet due to wave diffraction is also verified in the simulation. Both the upshift and broadening effects of the parallel spectrum of the wave-packet modify the parallel phase velocity and thus the linear absorption of LH waves by electron Landau resonance.
Design of experiments an introduction based on linear models
Morris, Max D
2011-01-01
IntroductionExample: rainfall and grassland Basic elements of an experimentExperiments and experiment-like studies Models and data analysisLinear Statistical ModelsLinear vector spaces Basic linear model The hat matrix, least-squares estimates, and design information matrixThe partitioned linear model The reduced normal equations Linear and quadratic forms Estimation and information Hypothesis testing and informationBlocking and informationCompletely Randomized DesignsIntroductionModels Matrix formulation Influence of design on estimation Influence of design on hypothesis testingRandomized Com
Self, B D; Moore, D S
1997-01-01
Infrared (IR) vibrational circular dichroism (VCD), absorption, and linear dichroism (LD) spectra of four homopolyribonucleotides, poly(rA), poly(rG), poly(rC), and poly(rU), have been calculated, in the 1750-1550 cm-1 spectral region, using the DeVoe polarizability theory. A newly derived algorithm, which approximates the Hilbert transform of imaginaries to reals, was used in the calculations to obtain real parts of oscillator polarizabilities associated with each normal mode. The calculated...
Sburlan, S. E.; Farr, W. H.
2011-01-01
Sub-band absorption at 1550 nm has been demonstrated and characterized on silicon Geiger mode detectors which normally would be expected to have no response at this wavelength. We compare responsivity measurements to singlephoton absorption for wavelengths slightly above the bandgap wavelength of silicon (approx. 1100 microns). One application for this low efficiency sub-band absorption is in deep space optical communication systems where it is desirable to track a 1030 nm uplink beacon on the same flight terminal detector array that monitors a 1550 nm downlink signal for pointingcontrol. The currently observed absorption at 1550 nm provides 60-70 dB of isolation compared to the response at 1064 nm, which is desirable to avoid saturation of the detector by scattered light from the downlink laser.
Linearized Functional Minimization for Inverse Modeling
Wohlberg, Brendt [Los Alamos National Laboratory; Tartakovsky, Daniel M. [University of California, San Diego; Dentz, Marco [Institute of Environmental Assessment and Water Research, Barcelona, Spain
2012-06-21
Heterogeneous aquifers typically consist of multiple lithofacies, whose spatial arrangement significantly affects flow and transport. The estimation of these lithofacies is complicated by the scarcity of data and by the lack of a clear correlation between identifiable geologic indicators and attributes. We introduce a new inverse-modeling approach to estimate both the spatial extent of hydrofacies and their properties from sparse measurements of hydraulic conductivity and hydraulic head. Our approach is to minimize a functional defined on the vectors of values of hydraulic conductivity and hydraulic head fields defined on regular grids at a user-determined resolution. This functional is constructed to (i) enforce the relationship between conductivity and heads provided by the groundwater flow equation, (ii) penalize deviations of the reconstructed fields from measurements where they are available, and (iii) penalize reconstructed fields that are not piece-wise smooth. We develop an iterative solver for this functional that exploits a local linearization of the mapping from conductivity to head. This approach provides a computationally efficient algorithm that rapidly converges to a solution. A series of numerical experiments demonstrates the robustness of our approach.
Checking for normality in linear mixed models
WU Ping; ZHU LiXing; FANG Yun
2012-01-01
Linear mixed models are popularly used to fit continuous longitudinal data,and the random effects are commonly assumed to have normal distribution.However,this assumption needs to be tested so that further analysis can be proceeded well.In this paper,we consider the Baringhaus-Henze-Epps-Pulley (BHEP) tests,which are based on an empirical characteristic function.Differing from their case,we consider the normality checking for the random effects which are unobservable and the test should be based on their predictors.The test is consistent against global alternatives,and is sensitive to the local alternatives converging to the null at a certain rate arbitrarily close to 1/(√)n where n is sample size.Furthermore,to overcome the problem that the limiting null distribution of the test is not tractable,we suggest a new method:use a conditional Monte Carlo test (CMCT) to approximate the null distribution,and then to simulate p-values.The test is compared with existing methods,the power is examined,and several examples are applied to illustrate the usefulness of our test in the analysis of longitudinal data.
Chen, Yujia; Wang, Kun; Gursoy, Doga; Soriano, Carmen; De Carlo, Francesco; Anastasio, Mark A.
2016-03-01
Propagation-based X-ray phase-contrast tomography (XPCT) provides the opportunity to image weakly absorbing objects and is being explored actively for a variety of important pre-clinical applications. Quantitative XPCT image reconstruction methods typically involve a phase retrieval step followed by application of an image reconstruction algorithm. Most approaches to phase retrieval require either acquiring multiple images at different object-to-detector distances or introducing simplifying assumptions, such as a single-material assumption, to linearize the imaging model. In order to overcome these limitations, a non-linear image reconstruction method has been proposed previously that jointly estimates the absorption and refractive properties of an object from XPCT projection data acquired at a single propagation distance, without the need to linearize the imaging model. However, the numerical properties of the associated non-convex optimization problem remain largely unexplored. In this study, computer simulations are conducted to investigate the feasibility of the joint reconstruction problem in practice. We demonstrate that the joint reconstruction problem is ill-posed and sensitive to system inconsistencies. Particularly, the method can generate accurate refractive index images only if the object is thin and has no phase-wrapping in the data. However, we also observed that, for weakly absorbing objects, the refractive index images reconstructed by the joint reconstruction method are, in general, more accurate than those reconstructed using methods that simply ignore the object's absorption.
Nonlinear Interaction of Elliptical Laser Beam with Collisional Plasma: Effect of Linear Absorption
Keshav, Walia; Sarabjit, Kaur
2016-01-01
In the present work, nonlinear interaction of elliptical laser beam with collisional plasma is studied by using paraxial ray approximation. Nonlinear differential equations for the beam width parameters of semi-major axis and semi-minor axis of elliptical laser beam have been set up and solved numerically to study the variation of beam width parameters with normalized distance of propagation. Effects of variation in absorption coefficient and plasma density on the beam width parameters are also analyzed. It is observed from the analysis that extent of self-focusing of beam increases with increase/decrease in plasma density/absorption coefficient.
Model averaging for semiparametric additive partial linear models
无
2010-01-01
To improve the prediction accuracy of semiparametric additive partial linear models(APLM) and the coverage probability of confidence intervals of the parameters of interest,we explore a focused information criterion for model selection among ALPM after we estimate the nonparametric functions by the polynomial spline smoothing,and introduce a general model average estimator.The major advantage of the proposed procedures is that iterative backfitting implementation is avoided,which thus results in gains in computational simplicity.The resulting estimators are shown to be asymptotically normal.A simulation study and a real data analysis are presented for illustrations.
Water Transport Models of Moisture Absorption and Sweat Discharge Yarns
WANG Fa-ming; ZHOU Xiao-hong; WANG Shan-yuan
2008-01-01
An important property of moisture absorption and sweat discharge yams is their water transport property. In the paper, two water transport models of moisture absorption and sweat discharge yams were developed to investigate the influence factors on their wicking rate. In parallel Column Pores Model, wicking rate is determined by the equivalent capillary radius R and length of the capillary tube L. In Pellets Accumulation Model, wicking rate is decided by the capillary radius r and length of the fiber unit assemble L0.
High-Level Analogue Fault Simulation Using Linear and Non-Linear Models
I. Bell
1999-12-01
Full Text Available A novel method for analogue high-level fault simulation (HLFS using linear and non-linear high-level fault models is presented. Our approach uses automated fault model synthesis and automated model selection for fault simulation. A speed up compared with transistor-level fault simulation can be achieved, whilst retaining both behavioural and fault coverage accuracy. The suggested method was verified in detail using short faults in a 10k state variable bandpass filter.
Dasari, Raghunath R; Sartin, Matthew M; Cozzuol, Matteo; Barlow, Stephen; Perry, Joseph W; Marder, Seth R
2011-04-21
Ruthenium phthalocyanines and naphthalocyanines with axial dendronised pyridine ligands show high solubility in a variety of solvents, and exhibit solid-state absorption spectra that are comparable to those obtained in dilute solution, making them interesting candidates for optical limiting in the visible. PMID:21399800
The mass attenuation and energy absorption coefficients are basic quantities used in calculations of photon energy transport and deposition for radiation dosimetry. This report describes a study of the concentration dependence of the attenuation of γ radiation of various energies by KCl solutions of different concentration. (author)
Equivalent linear damping characterization in linear and nonlinear force-stiffness muscle models.
Ovesy, Marzieh; Nazari, Mohammad Ali; Mahdavian, Mohammad
2016-02-01
In the current research, the muscle equivalent linear damping coefficient which is introduced as the force-velocity relation in a muscle model and the corresponding time constant are investigated. In order to reach this goal, a 1D skeletal muscle model was used. Two characterizations of this model using a linear force-stiffness relationship (Hill-type model) and a nonlinear one have been implemented. The OpenSim platform was used for verification of the model. The isometric activation has been used for the simulation. The equivalent linear damping and the time constant of each model were extracted by using the results obtained from the simulation. The results provide a better insight into the characteristics of each model. It is found that the nonlinear models had a response rate closer to the reality compared to the Hill-type models. PMID:26837750
Admissibilities of linear estimator in a class of linear models with a multivariate t error variable
无
2010-01-01
This paper discusses admissibilities of estimators in a class of linear models,which include the following common models:the univariate and multivariate linear models,the growth curve model,the extended growth curve model,the seemingly unrelated regression equations,the variance components model,and so on.It is proved that admissible estimators of functions of the regression coefficient β in the class of linear models with multivariate t error terms,called as Model II,are also ones in the case that error terms have multivariate normal distribution under a strictly convex loss function or a matrix loss function.It is also proved under Model II that the usual estimators of β are admissible for p 2 with a quadratic loss function,and are admissible for any p with a matrix loss function,where p is the dimension of β.
An online re-linearization scheme suited for Model Predictive and Linear Quadratic Control
Henriksen, Lars Christian; Poulsen, Niels Kjølstad
This technical note documents the equations for primal-dual interior-point quadratic programming problem solver used for MPC. The algorithm exploits the special structure of the MPC problem and is able to reduce the computational burden such that the computational burden scales with prediction...... horizon length in a linear way rather than cubic, which would be the case if the structure was not exploited. It is also shown how models used for design of model-based controllers, e.g. linear quadratic and model predictive, can be linearized both at equilibrium and non-equilibrium points, making the...
Recent Updates to the GEOS-5 Linear Model
Holdaway, Dan; Kim, Jong G.; Errico, Ron; Gelaro, Ronald; Mahajan, Rahul
2014-01-01
Global Modeling and Assimilation Office (GMAO) is close to having a working 4DVAR system and has developed a linearized version of GEOS-5.This talk outlines a series of improvements made to the linearized dynamics, physics and trajectory.Of particular interest is the development of linearized cloud microphysics, which provides the framework for 'all-sky' data assimilation.
LINEAR MODEL FOR NON ISOSCELES ABSORBERS
Previous analyses have assumed that wedge absorbers are triangularly shaped with equal angles for the two faces. In this case, to linear order, the energy loss depends only on the position in the direction of the face tilt, and is independent of the incoming angle. One can instead construct an absorber with entrance and exit faces facing rather general directions. In this case, the energy loss can depend on both the position and the angle of the particle in question. This paper demonstrates that and computes the effect to linear order
UNDERSTANDING THE APPLICABILITY OF LINEAR & NON-LINEAR MODELS USING A CASE-BASED STUDY
Gaurav Singh Thakur; Anubhav Gupta; Ankur Bhardwaj; Biju R Mohan
2014-01-01
This paper uses a case based study – “product sales estimation” on real-time data to help us understand the applicability of linear and non-linear models in machine learning and data mining. A systematic approach has been used here to address the given problem statement of sales estimation for a particular set of products in multiple categories by applying both linear and non-linear machine learning techniques on a data set of selected features from the original data set. Feature ...
Andersen, Per Kragh; Klein, John P.; Rosthøj, Susanne
2003-01-01
Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model......Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model...
Ebrahimipour, Bahareh Alsadat; Askari, Hassan Ranjbar; Ramezani, Ali Behjat
2016-09-01
The interlevel absorption coefficient of CdSe/ZnS and ZnS/CdSe core-shell Quantum Dot (QD) in luminescent solar concentrators (LSCs) is reported. By considering the quantum confinement effects, the wave functions and eigenenergies of electrons in the nonperturebative system consists of a core-shell QD have been numerically calculated under the frame work of effective-mass approximation by solving a three-dimensional Schrӧdinger equation. And then the absorption coefficient is obtained under density matrix approximation considering in the polymer sheets of the concentrator including the core-shell QDs. The effect of the hetero-structure geometry upon the energy spectrum and absorption coefficient associated to interlevel transitions was also considered. The results show that the core-shell QDs can absorb the photons with higher energy in solar spectrum as compared to the inverted core-shell. And with a small shell layer diameter, the core-shell QDs produce larger linear absorption coefficients and consequently higher efficiency values, however it is inversed for inverted core-shell QDs. The work described here gives a detailed insight into the promise of QD-based LSCs and the optoelectronic devices applications.
Rakheja, S; Gurram, R; Gouw, G J
1993-10-01
Hand-arm vibration (HAV) models serve as an effective tool to assess the vibration characteristics of the hand-tool system and to evaluate the attenuation performance of vibration isolation mechanisms. This paper describes a methodology to identify the parameters of HAV models, whether linear or nonlinear, using mechanical impedance data and a nonlinear programming based optimization technique. Three- and four-degrees-of-freedom (DOF) linear, piecewise linear and nonlinear HAV models are formulated and analyzed to yield impedance characteristics in the 5-1000 Hz frequency range. A local equivalent linearization algorithm, based upon the principle of energy similarity, is implemented to simulate the nonlinear HAV models. Optimization methods are employed to identify the model parameters, such that the magnitude and phase errors between the computed and measured impedance characteristics are minimum in the entire frequency range. The effectiveness of the proposed method is demonstrated through derivations of models that correlate with the measured X-axis impedance characteristics of the hand-arm system, proposed by ISO. The results of the study show that a linear model cannot predict the impedance characteristics in the entire frequency range, while a piecewise linear model yields an accurate estimation. PMID:8253830
Linear and Nonlinear Models of Agenda Setting in Television.
Brosius, Hans-Bernd; Kepplinger, Hans Mathias
1992-01-01
A content analysis of major German television news shows and 53 weekly surveys on 16 issues were used to compare linear and nonlinear models as ways to describe the relationship between media coverage and the public agenda. Results indicate that nonlinear models are in some cases superior to linear models in terms of explained variance. (34…
Integro-differential models for percutaneous drug absorption
Barbeiro, S.; Ferreira, J. A.
2007-01-01
In this paper we propose new mathematical models for percutaneous absorption of a drug. The new models are established by introducing, in the classical Fick's law, a memory term being the advection–diffusion equations of the classical models replaced by integro-differential equations. The well-posedness of the models is studied with Dirichlet, Neumann and natural boundary conditions. Methods for the computation of numerical solutions are proposed. Stability and convergence of the introduced m...
Exact linear rational expectations models: specification and estimation
Lars Peter Hansen; Thomas J. Sargent
1981-01-01
This paper describes how to specify and estimate rational expectations models in which there are exact linear relationships among variables and expectations of variables that the econometrician observes.
Error Control of Iterative Linear Solvers for Integrated Groundwater Models
Dixon, Matthew; Brush, Charles; Chung, Francis; Dogrul, Emin; Kadir, Tariq
2010-01-01
An open problem that arises when using modern iterative linear solvers, such as the preconditioned conjugate gradient (PCG) method or Generalized Minimum RESidual method (GMRES) is how to choose the residual tolerance in the linear solver to be consistent with the tolerance on the solution error. This problem is especially acute for integrated groundwater models which are implicitly coupled to another model, such as surface water models, and resolve both multiple scales of flow and temporal interaction terms, giving rise to linear systems with variable scaling. This article uses the theory of 'forward error bound estimation' to show how rescaling the linear system affects the correspondence between the residual error in the preconditioned linear system and the solution error. Using examples of linear systems from models developed using the USGS GSFLOW package and the California State Department of Water Resources' Integrated Water Flow Model (IWFM), we observe that this error bound guides the choice of a prac...
MODEL SELECTION FOR LOG-LINEAR MODELS OF CONTINGENCY TABLES
ZHAO Lincheng; ZHANG Hong
2003-01-01
In this paper, we propose an information-theoretic-criterion-based model selection procedure for log-linear model of contingency tables under multinomial sampling, and establish the strong consistency of the method under some mild conditions. An exponential bound of miss detection probability is also obtained. The selection procedure is modified so that it can be used in practice. Simulation shows that the modified method is valid. To avoid selecting the penalty coefficient in the information criteria, an alternative selection procedure is given.
Forecasting Volatility of Dhaka Stock Exchange: Linear Vs Non-linear models
Masudul Islam
2012-10-01
Full Text Available Prior information about a financial market is very essential for investor to invest money on parches share from the stock market which can strengthen the economy. The study examines the relative ability of various models to forecast daily stock indexes future volatility. The forecasting models that employed from simple to relatively complex ARCH-class models. It is found that among linear models of stock indexes volatility, the moving average model ranks first using root mean square error, mean absolute percent error, Theil-U and Linex loss function criteria. We also examine five nonlinear models. These models are ARCH, GARCH, EGARCH, TGARCH and restricted GARCH models. We find that nonlinear models failed to dominate linear models utilizing different error measurement criteria and moving average model appears to be the best. Then we forecast the next two months future stock index price volatility by the best (moving average model.
Response of a rotorcraft model with damping non-linearities
Tongue, B. H.
1985-11-01
The linearized equations of motion of a helicopter in contact with the ground have solutions which can be linearly stable or unstable, depending on the system parameters. The present study includes physical non-linearities in the helicopter model. This allows one to determine if a steady-state response exists and, if so, what the frequency and amplitude of the oscillations will be. In this way, one can determine how serious the linearly unstable operating regime is and whether destructive oscillations are possible when the system is in the linearly stable regime. The present analysis applies to helicopters having fully articulated rotors.
Injecting Abstract Interpretations into Linear Cost Models
David Cachera
2010-06-01
Full Text Available We present a semantics based framework for analysing the quantitative behaviour of programs with regard to resource usage. We start from an operational semantics equipped with costs. The dioid structure of the set of costs allows for defining the quantitative semantics as a linear operator. We then present an abstraction technique inspired from abstract interpretation in order to effectively compute global cost information from the program. Abstraction has to take two distinct notions of order into account: the order on costs and the order on states. We show that our abstraction technique provides a correct approximation of the concrete cost computations.
Employment of CB models for non-linear dynamic analysis
Klein, M. R. M.; Deloo, P.; Fournier-Sicre, A.
1990-01-01
The non-linear dynamic analysis of large structures is always very time, effort and CPU consuming. Whenever possible the reduction of the size of the mathematical model involved is of main importance to speed up the computational procedures. Such reduction can be performed for the part of the structure which perform linearly. Most of the time, the classical Guyan reduction process is used. For non-linear dynamic process where the non-linearity is present at interfaces between different structures, Craig-Bampton models can provide a very rich information, and allow easy selection of the relevant modes with respect to the phenomenon driving the non-linearity. The paper presents the employment of Craig-Bampton models combined with Newmark direct integration for solving non-linear friction problems appearing at the interface between the Hubble Space Telescope and its solar arrays during in-orbit maneuvers. Theory, implementation in the FEM code ASKA, and practical results are shown.
UNDERSTANDING THE APPLICABILITY OF LINEAR & NON-LINEAR MODELS USING A CASE-BASED STUDY
Gaurav Singh Thakur
2014-11-01
Full Text Available This paper uses a case based study – “product sales estimation” on real-time data to help us understand the applicability of linear and non-linear models in machine learning and data mining. A systematic approach has been used here to address the given problem statement of sales estimation for a particular set of products in multiple categories by applying both linear and non-linear machine learning techniques on a data set of selected features from the original data set. Feature selection is a process that reduces the dimensionality of the data set by excluding those features which contribute minimal to the prediction of the dependent variable. The next step in this process is training the model that is done using multiple techniques from linear & non-linear domains, one of the best ones in their respective areas. Data Remodeling has then been done to extract new features from the data set by changing the structure of the dataset & the performance of the models is checked again. Data Remodeling often plays a very crucial and important role in boosting classifier accuracies by changing the properties of the given dataset. We then try to explore and analyze the various reasons due to which one model performs better than the other & hence try and develop an understanding about the applicability of linear & non-linear machine learning models. The target mentioned above being our primary goal, we also aim to find the classifier with the best possible accuracy for product sales estimation in the given scenario.
Gauged linear sigma model for exotic five-brane
We study an N=(4,4) supersymmetric gauged linear sigma model which gives rise to the nonlinear sigma model for multi-centered KK-monopoles. We find a new T-duality transformation of the model even in the presence of F-terms. Performing T-duality, we find the gauged linear sigma model whose IR limit describes the exotic 522-brane with B-field
Multivariate statistical modelling based on generalized linear models
Fahrmeir, Ludwig
1994-01-01
This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account to have on their desks. "The basic aim of the authors is to bring together and review a large part of recent advances in statistical modelling of m...
Incorporating tissue absorption and scattering in rapid ultrasound beam modeling
Christensen, Douglas; Almquist, Scott
2013-02-01
We have developed a new approach for modeling the propagation of an ultrasound beam in inhomogeneous tissues such as encountered with high-intensity focused ultrasound (HIFU) for treatment of various diseases. This method, called the hybrid angular spectrum (HAS) approach, alternates propagation steps between the space and the spatial frequency domains throughout the inhomogeneous regions of the body; the use of spatial Fourier transforms makes this technique considerably faster than other modeling approaches (about 10 sec for a 141 x 141 x 121 model). In HIFU thermal treatments, the acoustic absorption property of the tissues is of prime importance since it leads to temperature rise and the achievement of desired thermal dose at the treatment site. We have recently added to the HAS method the capability of independently modeling tissue absorption and scattering, the two components of acoustic attenuation. These additions improve the predictive value of the beam modeling and more accurately describes the thermal conditions expected during a therapeutic ultrasound exposure. Two approaches to explicitly model scattering were developed: one for scattering sizes smaller than a voxel, and one when the scattering scale is several voxels wide. Some anatomically realistic examples that demonstrate the importance of independently modeling absorption and scattering are given, including propagation through the human skull for noninvasive brain therapy and in the human breast for treatment of breast lesions.
Bao Xue ZHANG; Bai Sen LIU; Chang Yu LU
2004-01-01
Consider the partitioned linear regression model A = (y, X1β1 + X2β2, σ2V) and its four reduced linear models, where y is an n × 1 observable random vector with E(y) = Xβ and dispersion matrix Var(y) = σ2V, where σ2 is an unknown positive scalar, V is an n × n known symmetric nonnegative definite matrix, X = (X1: X2) is an n× (p+q) known design matrix with rank(X) = r ≤ (p+q),andβ = (β'1:β'2)' withβ1 andβ2 being p × 1 and q × 1 vectors of unknown parameters, respectively. In this article the formulae for the differences between the best linear unbiased estimators of M2X1β1under the model A and its best linear unbiased estimators under the reduced linear models of A are given,where M2 = I - X2X2+. Furthermore, the necessary and sufficient conditions for the equalities between the best linear unbiased estimators of M2X1β1 under the model A and those under its reduced linear models are established. Lastly, we also study the connections between the model A and its linear transformation model.
A unifying review of linear gaussian models.
Roweis, S; Ghahramani, Z
1999-02-15
Factor analysis, principal component analysis, mixtures of gaussian clusters, vector quantization, Kalman filter models, and hidden Markov models can all be unified as variations of unsupervised learning under a single basic generative model. This is achieved by collecting together disparate observations and derivations made by many previous authors and introducing a new way of linking discrete and continuous state models using a simple nonlinearity. Through the use of other nonlinearities, we show how independent component analysis is also a variation of the same basic generative model. We show that factor analysis and mixtures of gaussians can be implemented in autoencoder neural networks and learned using squared error plus the same regularization term. We introduce a new model for static data, known as sensible principal component analysis, as well as a novel concept of spatially adaptive observation noise. We also review some of the literature involving global and local mixtures of the basic models and provide pseudocode for inference and learning for all the basic models. PMID:9950734
Model galactic coronae: Ionization structure and absorption-line spectra
We describe a general model for a gaseous galactic corona, and demonstrate that it is in harmony with a variety of observational and theoretical constraints. We then compute the ionization equilibria of H, He, C, N, O, Si, and S atoms in the corona and determine the strengths of resonance absorption lines arising therein. To this end, we obtain approximate cross sections for ionization of the heavy-element ions by photons of energy E/sub γ/< or =100 eV.We use our results first to discuss the expected absorption spectrum of our Galaxy's corona. Subsequently, we discuss in detail the relevance of our computed equilibria to the suggestion that galactic coronae produce some redshift systems in quasar absorption spectra. Because our model coronae are not isothermal, the ionization structure existing along various lines of sight through them is not in accord with the concept of ''reasonable ionization equilibrium'': a concept assumed to be valid in most analyses of quasar spectra. However, our calculations indicate that typically one well-established redshift system in each quasar absorption spectrum could arise in the corona of an intervening galaxy. This is the number expected from statistical arguments if quasar redshifts are fully cosmological in origin
Linear Latent Force Models using Gaussian Processes
Álvarez, Mauricio A; Lawrence, Neil D
2011-01-01
Purely data driven approaches for machine learning present difficulties when data is scarce relative to the complexity of the model or when the model is forced to extrapolate. On the other hand, purely mechanistic approaches need to identify and specify all the interactions in the problem at hand (which may not be feasible) and still leave the issue of how to parameterize the system. In this paper, we present a hybrid approach using Gaussian processes and differential equations to combine data driven modelling with a physical model of the system. We show how different, physically-inspired, kernel functions can be developed through sensible, simple, mechanistic assumptions about the underlying system. The versatility of our approach is illustrated with three case studies from motion capture, computational biology and geostatistics.
Absorption Cycle Heat Pump Model for Control Design
Vinther, Kasper; Just Nielsen, Rene; Nielsen, Kirsten Mølgaard;
2015-01-01
actual heat pump located at a larger district heating plant. The model is implemented in Modelica and is based on energy and mass balances, together with thermodynamic property functions for LiBr and water and staggered grid representations for heat exchangers. Model parameters have been fitted to......Heat pumps have recently received increasing interest due to green energy initiatives and increasing energy prices. In this paper, a nonlinear dynamic model of a single-effect LiBr-water absorption cycle heat pump is derived for simulation and control design purposes. The model is based on an...
NON-LINEAR SOIL MODELS FOR PIPELINE AND RISER ANALYSIS
Irman, Arifian Agusta
2015-01-01
This thesis describes the development and application of non-linear soil models in pipeline and riser design. A non-linear soil model is typically employed when investigating a complex pipe-soil interaction problem. Two main pipe-soil interactions are frequently studied: the vertical pipe-soil interaction at the touchdown point of the steel catenary riser (SCR) during cyclic heave motion, and the lateral pipe-soil interaction during the pipeline s lateral buckling. Mathematical models for...
Neural network modelling of non-linear hydrological relationships
Abrahart, R. J.; See, L. M.
2007-09-01
Two recent studies have suggested that neural network modelling offers no worthwhile improvements in comparison to the application of weighted linear transfer functions for capturing the non-linear nature of hydrological relationships. The potential of an artificial neural network to perform simple non-linear hydrological transformations under controlled conditions is examined in this paper. Eight neural network models were developed: four full or partial emulations of a recognised non-linear hydrological rainfall-runoff model; four solutions developed on an identical set of inputs and a calculated runoff coefficient output. The use of different input combinations enabled the competencies of solutions developed on a reduced number of parameters to be assessed. The selected hydrological model had a limited number of inputs and contained no temporal component. The modelling process was based on a set of random inputs that had a uniform distribution and spanned a modest range of possibilities. The initial cloning operations permitted a direct comparison to be performed with the equation-based relationship. It also provided more general information about the power of a neural network to replicate mathematical equations and model modest non-linear relationships. The second group of experiments explored a different relationship that is of hydrological interest; the target surface contained a stronger set of non-linear properties and was more challenging. Linear modelling comparisons were performed against traditional least squares multiple linear regression solutions developed on identical datasets. The reported results demonstrate that neural networks are capable of modelling non-linear hydrological processes and are therefore appropriate tools for hydrological modelling.
Generalized Linear Models with Applications in Engineering and the Sciences
Myers, Raymond H; Vining, G Geoffrey; Robinson, Timothy J
2012-01-01
Praise for the First Edition "The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of applied science should buy it and experience the excitement of these new approaches to familiar activities."-Technometrics Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition continues to provide a clear introduction to the theoretical foundations and key applications of generalized linear models (GLMs). Ma
Linear Sigma Models for Open Strings
We formulate and study a class of massive N = 2 supersymmetric gauge field theories coupled to boundary degrees of freedom on the strip. For some values of the parameters, the infrared limits of these theories can be interpreted as open string sigma models describing D-branes in large-radius Calabi-Yau compactifications. For other values of the parameters, these theories flow to CFTs describing branes in more exotic, non-geometric phases of the Calabi-Yau moduli space such as the Landau-Ginzburg orbifold phase. Some simple properties of the branes (like large radius monodromies and spectra of worldvolume excitations) can be computed in our model. We also provide simple worldsheet models of the transitions which occur at loci of marginal stability, and of Higgs-Coulomb transitions
Linear sigma models for open strings
We formulate and study a class of massive N=2 supersymmetric gauge field theories coupled to boundary degrees of freedom on the strip. For some values of the parameters, the infrared limits of these theories can be interpreted as open string sigma models describing D-branes in large-radius Calabi-Yau compactifications. For other values of the parameters, these theories flow to CFTs describing branes in more exotic, non-geometric phases of the Calabi-Yau moduli space such as the Landau-Ginzburg orbifold phase. Some simple properties of the branes (like large radius monodromies and spectra of worldvolume excitations) can be computed in our model. We also provide simple worldsheet models of the transitions which occur at loci of marginal stability, and of Higgs-Coulomb transitions. (author)
Non-linear protocell models: synchronization and chaos
Filisetti, A.; Serra, R.; Carletti, T.; Villani, M.; Poli, I.
2010-09-01
We consider generic protocells models allowing linear and non-linear kinetics for the main involved chemical reactions. We are interested in understanding if and how the protocell division and the metabolism do synchronise to give rise to sustainable evolution of the protocell.
Model Reduction by Moment Matching for Linear Switched Systems
Bastug, Mert; Petreczky, Mihaly; Wisniewski, Rafal;
2014-01-01
A moment-matching method for the model reduction of linear switched systems (LSSs) is developed. The method is based based upon a partial realization theory of LSSs and it is similar to the Krylov subspace methods used for moment matching for linear systems. The results are illustrated by numerical...
Linear Time-Invariant Models of Non-Linear Time-Varying Systems
Ljung, Lennart
2001-01-01
The standard machinery for system identification of linear time invariant (LTI) models delivers a nominal model and a confidence (uncertainty) region around it, based on (second order moment) residual analysis and covariance estimation. In most cases this gives an uncertainty region that tends to zero as more and more data become available, even if the true system is non-linear and/or time-varying. In this paper, the reasons for this are displayed, and a characterization of the limit LTI mode...
Bayesian Subset Modeling for High-Dimensional Generalized Linear Models
Liang, Faming
2013-06-01
This article presents a new prior setting for high-dimensional generalized linear models, which leads to a Bayesian subset regression (BSR) with the maximum a posteriori model approximately equivalent to the minimum extended Bayesian information criterion model. The consistency of the resulting posterior is established under mild conditions. Further, a variable screening procedure is proposed based on the marginal inclusion probability, which shares the same properties of sure screening and consistency with the existing sure independence screening (SIS) and iterative sure independence screening (ISIS) procedures. However, since the proposed procedure makes use of joint information from all predictors, it generally outperforms SIS and ISIS in real applications. This article also makes extensive comparisons of BSR with the popular penalized likelihood methods, including Lasso, elastic net, SIS, and ISIS. The numerical results indicate that BSR can generally outperform the penalized likelihood methods. The models selected by BSR tend to be sparser and, more importantly, of higher prediction ability. In addition, the performance of the penalized likelihood methods tends to deteriorate as the number of predictors increases, while this is not significant for BSR. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Extended Linear Models with Gaussian Priors
Quinonero, Joaquin
2002-01-01
on the parameters. The Relevance Vector Machine, introduced by Tipping, is a particular case of such a model. I give the detailed derivations of the expectation-maximisation (EM) algorithm used in the training. These derivations are not found in the literature, and might be helpful for newcomers....
Random effect selection in generalised linear models
Denwood, Matt; Houe, Hans; Forkman, Björn;
We analysed abattoir recordings of meat inspection codes with possible relevance to onfarm animal welfare in cattle. Random effects logistic regression models were used to describe individual-level data obtained from 461,406 cattle slaughtered in Denmark. Our results demonstrate that the largest...
New analytical solution to calculate linear absorption coefficients of beta radiations.
Švec, Anton
2015-08-01
The paper deals with an alternative model of beta radiation transmissions through attenuation layers and brings another analytical description of this phenomenon. The model is validated with a reliable data set and brings a possibility to calculate characteristic material parameters with low uncertainties. Using no correction factors, these calculations can be considered fundamental and inspiring for further research in the field. PMID:25989183
Genetic parameters for racing records in trotters using linear and generalized linear models.
Suontama, M; van der Werf, J H J; Juga, J; Ojala, M
2012-09-01
Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success
Forecasting telecommunications data with linear models
Madden, Gary G; Tan, Joachim
2007-01-01
For telecommunication companies to successfully manage their business, companies rely on mapping future trends and usage patterns. However, the evolution of telecommunications technology and systems in the provision of services renders imperfections in telecommunications data and impinges on a company’s’ ability to properly evaluate and plan their business. ITU Recommendation E.507 provides a selection of econometric models for forecasting these trends. However, no specific guidance is given....
Remark on: the neutron spherical optical-model absorption.
Smith, A. B.; Nuclear Engineering Division
2007-06-30
The energy-dependent behavior of the absorption term of the spherical neutron optical potential for doubly magic {sup 208}Pb and the neighboring {sup 209}Bi is examined. These considerations suggest a phenomenological model that results in an intuitively attractive energy dependence of the imaginary potential that provides a good description of the observed neutron cross sections and that is qualitatively consistent with theoretical concepts. At the same time it provides an alternative to some of the arbitrary assumptions involved in many conventional optical-model interpretations reported in the literature and reduces the number of the parameters of the model.
Kokaly, R.F.; Clark, R.N.
1999-01-01
We develop a new method for estimating the biochemistry of plant material using spectroscopy. Normalized band depths calculated from the continuum-removed reflectance spectra of dried and ground leaves were used to estimate their concentrations of nitrogen, lignin, and cellulose. Stepwise multiple linear regression was used to select wavelengths in the broad absorption features centered at 1.73 ??m, 2.10 ??m, and 2.30 ??m that were highly correlated with the chemistry of samples from eastern U.S. forests. Band depths of absorption features at these wavelengths were found to also be highly correlated with the chemistry of four other sites. A subset of data from the eastern U.S. forest sites was used to derive linear equations that were applied to the remaining data to successfully estimate their nitrogen, lignin, and cellulose concentrations. Correlations were highest for nitrogen (R2 from 0.75 to 0.94). The consistent results indicate the possibility of establishing a single equation capable of estimating the chemical concentrations in a wide variety of species from the reflectance spectra of dried leaves. The extension of this method to remote sensing was investigated. The effects of leaf water content, sensor signal-to-noise and bandpass, atmospheric effects, and background soil exposure were examined. Leaf water was found to be the greatest challenge to extending this empirical method to the analysis of fresh whole leaves and complete vegetation canopies. The influence of leaf water on reflectance spectra must be removed to within 10%. Other effects were reduced by continuum removal and normalization of band depths. If the effects of leaf water can be compensated for, it might be possible to extend this method to remote sensing data acquired by imaging spectrometers to give estimates of nitrogen, lignin, and cellulose concentrations over large areas for use in ecosystem studies.We develop a new method for estimating the biochemistry of plant material using
The linear model and hypothesis a general unifying theory
Seber, George
2015-01-01
This book provides a concise and integrated overview of hypothesis testing in four important subject areas, namely linear and nonlinear models, multivariate analysis, and large sample theory. The approach used is a geometrical one based on the concept of projections and their associated idempotent matrices, thus largely avoiding the need to involve matrix ranks. It is shown that all the hypotheses encountered are either linear or asymptotically linear, and that all the underlying models used are either exactly or asymptotically linear normal models. This equivalence can be used, for example, to extend the concept of orthogonality in the analysis of variance to other models, and to show that the asymptotic equivalence of the likelihood ratio, Wald, and Score (Lagrange Multiplier) hypothesis tests generally applies.
Optimization for decision making linear and quadratic models
Murty, Katta G
2010-01-01
While maintaining the rigorous linear programming instruction required, Murty's new book is unique in its focus on developing modeling skills to support valid decision-making for complex real world problems, and includes solutions to brand new algorithms.
On D-branes from gauged linear sigma models
We study both A-type and B-type D-branes in the gauged linear sigma model by considering worldsheets with boundary. The boundary conditions on the matter and vector multiplet fields are first considered in the large-volume phase/non-linear sigma model limit of the corresponding Calabi-Yau manifold, where we find that we need to add a contact term on the boundary. These considerations enable to us to derive the boundary conditions in the full gauged linear sigma model, including the addition of the appropriate boundary contact terms, such that these boundary conditions have the correct non-linear sigma model limit. Most of the analysis is for the case of Calabi-Yau manifolds with one Kaehler modulus (including those corresponding to hypersurfaces in weighted projective space), though we comment on possible generalisations
The Non-Linear Relationship between Silicate Absorption Depth and IR Extinction in Dense Clouds
Chiar, Jean E.; Pendleton, Y.; Ennico, K.; Boogert, A.; Greene, T.; Lada, C.; Roellig, T.; Tielens, A.; Werner, M.; Whittet, D.
2006-12-01
Interstellar silicates are likely to be a part of all grains responsible for extinction in the diffuse interstellar medium (ISM) and dense clouds. A correlation between visual extinction (Av) and the depth of the 9.7 mu silicate feature (measured as optical depth, tau(9.7)) is expected if the dust species are well mixed. In the diffuse ISM, such a correlation is observed for lines of sight in the solar neighborhood. A previous study of the silicate absorption feature in the Taurus dark cloud showed a tendency for the correlation to break down at high Av (Whittet et al. 1988, MNRAS, 233, 321), but the scatter was large. We have acquired Spitzer Infrared Spectrograph data of several lines of sight in the IC 5146, Barnard 68, Chameleon I and Serpens dense clouds. To eliminate any uncertainties associated with adopting a specific extinction law, we investigated the relationship between tau(9.7) and E(J-K). Our data set spans E(J-K) between 0.3 and 8 mag (Av=between 2-35 mag.). All lines of sight show the 9.7 mu silicate feature. For E(J-K) greater than about 2 mag, tau(9.7) levels off, much like the trend observed in the Taurus data. There are two exceptions: one line of sight in Serpens, with E(J-K) 4 mag lies on the diffuse ISM line. Another line of sight with E(J-K) 8 mag, also in Serpens, lies well below the diffuse ISM line, but well above the “flat” trend of the other dense cloud sources. This particular line of sight also has a high ice column relative to the amount of visual/infrared extinction. The cause of the “flat” trend exhibited by most of the dense cloud points is undetermined. However, in general, it is unlikely that ice mantles would have any effect on the measured silicate feature since ices are transparent in the 10 mu region.
Bootstrap and Wild Bootstrap for High Dimensional Linear Models
Mammen, Enno
1993-01-01
In this paper two bootstrap procedures are considered for the estimation of the distribution of linear contrasts and of F-test statistics in high dimensional linear models. An asymptotic approach will be chosen where the dimension p of the model may increase for sample size $n\\rightarrow\\infty$. The range of validity will be compared for the normal approximation and for the bootstrap procedures. Furthermore, it will be argued that the rates of convergence are different for the bootstrap proce...
Graphical Log-linear Models: Fundamental Concepts and Applications
Gauraha, Niharika
2016-01-01
We present a comprehensive study of graphical log-linear models for contingency tables. High dimensional contingency tables arise in many areas such as computational biology, collection of survey and census data and others. Analysis of contingency tables involving several factors or categorical variables is very hard. To determine interactions among various factors, graphical and decomposable log-linear models are preferred. First, we explore connections between the conditional independence i...
Hydrodynamic model, simulation and linear control for Cormoran-AUV
González Agudelo, Julián; Benezra, Andreina; Gomáriz Castro, Spartacus; Garcia, Albert
2011-01-01
This work shows the mathematic calculation for obtention of a Cormoran-AUV hydrodynamic model, it also shows a linar control design for a path tracking. The model has been simplified to three degrees of freedom of movement and the whole system has been simulated using Matlab Simulink Software. The system has been linearizated for different velocities to design a linear control for each one of them. However, all resulting systems can be controlled by a unique linear control due charac...
Optimal Scaling of Interaction Effects in Generalized Linear Models
2007-01-01
Multiplicative interaction models, such as Goodman's RC(M) association models, can be a useful tool for analyzing the content of interaction effects. However, most models for interaction effects are only suitable for data sets with two or three predictor variables. Here, we discuss an optimal scaling model for analyzing the content of interaction effects in generalized linear models with any number of categorical predictor variables. This model, which we call the optimal scaling of interactio...
Optimal Scaling of Interaction Effects in Generalized Linear Models
van Rosmalen, Joost; Koning, Alex; Groenen, Patrick
2007-01-01
textabstractMultiplicative interaction models, such as Goodman's RC(M) association models, can be a useful tool for analyzing the content of interaction effects. However, most models for interaction effects are only suitable for data sets with two or three predictor variables. Here, we discuss an optimal scaling model for analyzing the content of interaction effects in generalized linear models with any number of categorical predictor variables. This model, which we call the optimal scaling o...
An I(2) Cointegration Model with Piecewise Linear Trends
Kurita, Takamitsu; Nielsen, Heino Bohn; Rahbek, Anders Christian
This paper presents likelihood analysis of the I(2) cointegrated vector autoregression with piecewise linear deterministic terms. Limiting behavior of the maximum likelihood estimators are derived, which is used to further derive the limiting distribution of the likelihood ratio statistic for the...... cointegration ranks, extending the result for I(2) models with a linear trend in Nielsen and Rahbek (2007) and for I(1) models with piecewise linear trends in Johansen, Mosconi, and Nielsen (2000). The provided asymptotic theory extends also the results in Johansen, Juselius, Frydman, and Goldberg (2009) where...
Generalized linear mixed models modern concepts, methods and applications
Stroup, Walter W
2012-01-01
PART I The Big PictureModeling BasicsWhat Is a Model?Two Model Forms: Model Equation and Probability DistributionTypes of Model EffectsWriting Models in Matrix FormSummary: Essential Elements for a Complete Statement of the ModelDesign MattersIntroductory Ideas for Translating Design and Objectives into ModelsDescribing ""Data Architecture"" to Facilitate Model SpecificationFrom Plot Plan to Linear PredictorDistribution MattersMore Complex Example: Multiple Factors with Different Units of ReplicationSetting the StageGoals for Inference with Models: OverviewBasic Tools of InferenceIssue I: Data
A diffusion-diffusion model for percutaneous drug absorption.
Kubota, K; Ishizaki, T
1986-08-01
Several theories describing percutaneous drug absorption have been proposed, incorporating the mathematical solutions of differential equations describing percutaneous drug absorption processes where the vehicle and skin are regarded as simple diffusion membranes. By a solution derived from Laplace transforms, the mean residence time MRT and the variance of the residence time VRT in the vehicle are expressed as simple elementary functions of the following five pharmacokinetic parameters characterizing the percutaneous drug absorption: kd, which is defined as the normalized diffusion coefficient of the skin, kc, which is defined as the normalized skin-capillary boundary clearance, the apparent length of diffusion of the skin 1d, the effective length of the vehicle lv, and the diffusion coefficient of the vehicle Dv. All five parameters can be obtained by the methods proposed here. Results of numerical computation indicate that: concentration-distance curves in the vehicle and skin approximate two curves which are simply expressed using trigonometric functions when sufficient time elapses after an ointment application; the most suitable condition for the assumption that the concentration of a drug in the uppermost epidermis can be considered unchanged is the case where the partition coefficient between vehicle and skin is small, and the constancy of drug concentration is even more valid when the effective length of the vehicle is large; and the amount of a drug in the vehicle or skin and the flow rate of the drug from vehicle into skin or from skin into blood becomes linear on a semilogarithmic scale, and the slopes of those lines are small when Dv is small, when the partition coefficient between vehicle and skin is small, when lv is large, or when kc is small. A simple simulation method is also proposed using a biexponential for the concentration-time curve for the skin near the skin-capillary boundary, that is, the flow rate-time curve for drug passing from skin
Scaling and linear response in the GOY model
Kadanoff, Leo; Lohse, Detlef; Schörghofer, Norbert
1997-01-01
The GOY model is a model for turbulence in which two conserved quantities cascade up and down a linear array of shells. When the viscosity parameter, small nu, Greek, is small the model has a qualitative behavior which is similar to the Kolmogorov theories of turbulence. Here a static solution to th
Linear latent variable models: the lava-package
Holst, Klaus Kähler; Budtz-Jørgensen, Esben
2013-01-01
An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features are...
Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian
2014-01-01
benchmark, as this type is frequently used, and has the lowest amount of constraints of the three. A comparison of the optimised operation of a number of units shows significant differences between the three methods. Compared to the reference, the use of binary integer variables, increases operation of...... differences and differences between the solution found by each optimisation method. One of the investigated approaches utilises LP (linear programming) for optimisation, one uses LP with binary operation constraints, while the third approach uses NLP (non-linear programming). The LP model is used as a...
Absorption lookup tables in the radiative transfer model ARTS
We describe the lookup table approach that is used to store pre-calculated absorption data in the radiative transfer model ARTS. The table stores absorption cross sections as a function of frequency, pressure, temperature, and the water vapor volume mixing ratio, where the last dimension is only included for those gas species that require it. The table is used together with an extraction strategy, which uses polynomial interpolation, with recommended interpolation orders between five and seven. We also derived recommended default settings for grid spacings and interpolation orders, and verified that the approach gives very accurate results with these default settings. The tested instrument setups were for AMSU-B, HIRS, and Odin, three well-known satellite remote sensing instruments covering a wide range of frequencies and viewing geometries. Errors introduced by the lookup table were found to be always below a few millikelvin, in terms of the simulated brightness temperature.
A dynamic model of digestion and absorption in pigs
Strathe, Anders Bjerring; Danfær, Allan Christian; Chwalibog, Andrzej
2008-01-01
The paper describes and evaluates the construction of a mathematical model to study the kinetics of digestion and absorption in growing pigs. The core of the model is based on a compartmental structure, which divides the gastro-intestinal tract into four anatomical segments: the stomach, two parts...... of the small intestine and the large intestine. Within the large intestine, a microbial sub compartment is also considered. In each of these segments, the major organic nutrients are considered: dietary protein, endogenous protein, amino acids, non-amino acid and non-protein nitrogen, lipids, fatty acids...
Models of ionospheric VLF absorption of powerful ground based transmitters
İnan, Umran Savaş; Cohen, M. B; Lehtinen, N. G
2012-01-01
Models of ionospheric VLF absorption of powerful ground based transmitters M. B. Cohen,1 N. G. Lehtinen,1 and U. S. Inan1,2 Received 5 November 2012; accepted 16 November 2012; published 29 December 2012. [1] Ground based Very Low Frequency (VLF, 3–30 kHz) radio transmitters play a role in precipitation of energetic Van Allen electrons. Initial analyses of the contribution of VLF transmitters to radiation belt losses were based on early models of trans-ionospheric prop...
Phase II monitoring of auto-correlated linear profiles using linear mixed model
Narvand, A.; Soleimani, P.; Raissi, Sadigh
2013-05-01
In many circumstances, the quality of a process or product is best characterized by a given mathematical function between a response variable and one or more explanatory variables that is typically referred to as profile. There are some investigations to monitor auto-correlated linear and nonlinear profiles in recent years. In the present paper, we use the linear mixed models to account autocorrelation within observations which is gathered on phase II of the monitoring process. We undertake that the structure of correlated linear profiles simultaneously has both random and fixed effects. The work enhanced a Hotelling's T 2 statistic, a multivariate exponential weighted moving average (MEWMA), and a multivariate cumulative sum (MCUSUM) control charts to monitor process. We also compared their performances, in terms of average run length criterion, and designated that the proposed control charts schemes could effectively act in detecting shifts in process parameters. Finally, the results are applied on a real case study in an agricultural field.
Quasilinear electron cyclotron absorption in a slab model for TBR-2
The electron cyclotron radiation generated by a gyrotron of operating frequency f = 35 GHz and power of 60 kW is used for heating and current drive experiments in the tokamak TBR-2 a project currently under study. A quasilinear code, that contains a self-consistent diffusion coefficient for electron cyclotron waves, averaged over tokamak magnetic surfaces, and includes collisions by means of a linearized Fokker-Planck collison term was developed. This code is applied to a slab model for TBR-2, supposed with an initial current presenting features of lower hybrid generated currents. A numerical analysis of two situations with good absorption is done. (author)
Distributed Lag Linear and Non-Linear Models in R: The Package dlnm
Antonio Gasparrini
2011-08-01
Full Text Available Distributed lag non-linear models (DLNMs represent a modeling framework to flexibly describe associations showing potentially non-linear and delayed effects in time series data. This methodology rests on the definition of a crossbasis, a bi-dimensional functional space expressed by the combination of two sets of basis functions, which specify the relationships in the dimensions of predictor and lags, respectively. This framework is implemented in the R package dlnm, which provides functions to perform the broad range of models within the DLNM family and then to help interpret the results, with an emphasis on graphical representation. This paper offers an overview of the capabilities of the package, describing the conceptual and practical steps to specify and interpret DLNMs with an example of application to real data.
In this paper the simultaneous effect of hydrostatic pressure and Rashba spin–orbit interaction on intraband linear and nonlinear light absorption has been investigated in cylindrical quantum ring. The one electron energy spectrum has been found using the effective mass approximation and diagonalization procedure. We have found that the Rashba interaction can lead both to the blue- or to the red-shift of the absorption spectrum depending on the transitions character, while the only red-shift is observed due to the hydrostatic pressure. - Highlights: ► The effects of hydrostatic pressure and spin–orbit coupling are investigated for quantum ring. ► The non-linear absorption coefficient is calculated. ► The hydrostatic pressure leads to the decrease in the absorption coefficient. ► Spin–orbit coupling weakens some transitions and strengthens others.
Linear approximation model network and its formation via evolutionary computation
Yun Li; Kay Chen Tan
2000-04-01
To overcome the deficiency of `local model network' (LMN) techniques, an alternative `linear approximation model' (LAM) network approach is proposed. Such a network models a nonlinear or practical system with multiple linear models fitted along operating trajectories, where individual models are simply networked through output or parameter interpolation. The linear models are valid for the entire operating trajectory and hence overcome the local validity of LMN models, which impose the predetermination of a scheduling variable that predicts characteristic changes of the nonlinear system. LAMs can be evolved fromsampled step response data directly, eliminating the need forlocal linearisation upon a pre-model using derivatives of the nonlinear system. The structural difference between a LAM network and an LMN isthat the overall model of the latteris a parameter-varying system and hence nonlinear,while the formerremains linear time-invariant (LTI). Hence, existing LTI and transfer function theory applies to a LAM network, which is therefore easy to use for control system design. Validation results show that the proposed method offers a simple, transparent and accurate multivariable modelling technique for nonlinear systems.
Computer modeling of batteries from non-linear circuit elements
Waaben, S.; Federico, J.; Moskowitz, I.
1983-01-01
A simple non-linear circuit model for battery behavior is given. It is based on time-dependent features of the well-known PIN change storage diode, whose behavior is described by equations similar to those associated with electrochemical cells. The circuit simulation computer program ADVICE was used to predict non-linear response from a topological description of the battery analog built from advice components. By a reasonable choice of one set of parameters, the circuit accurately simulates a wide spectrum of measured non-linear battery responses to within a few millivolts.
Estimation and variable selection for generalized additive partial linear models
Wang, Li
2011-08-01
We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration. © Institute of Mathematical Statistics, 2011.
Non-linear calibration models for near infrared spectroscopy
Ni, Wangdong; Nørgaard, Lars; Mørup, Morten
2014-01-01
Different calibration techniques are available for spectroscopic applications that show nonlinear behavior. This comprehensive comparative study presents a comparison of different nonlinear calibration techniques: kernel PLS (KPLS), support vector machines (SVM), least-squares SVM (LS-SVM......-linear models on linear problems, robustness to small or medium sample sets, and robustness to pre-processing, are discussed. The results suggest that GPR and BANN are powerful and promising methods for handling linear as well as nonlinear systems, even when the data sets are moderately small. The LS-SVM is...
Vaccination strategies for SEIR models using feedback linearization. Preliminary results
De la Sen, M; Alonso-Quesada, S
2011-01-01
A linearization-based feedback-control strategy for a SEIR epidemic model is discussed. The vaccination objective is the asymptotically tracking of the removed-by-immunity population to the total population while achieving simultaneously the remaining population (i.e. susceptible plus infected plus infectious) to asymptotically tend to zero. The disease controlpolicy is designed based on a feedback linearization technique which provides a general method to generate families of vaccination policies with sound technical background.
Performance modeling and prediction for linear algebra algorithms
Iakymchuk, Roman
2012-01-01
This dissertation incorporates two research projects: performance modeling and prediction for dense linear algebra algorithms, and high-performance computing on clouds. The first project is focused on dense matrix computations, which are often used as computational kernels for numerous scientific applications. To solve a particular mathematical operation, linear algebra libraries provide a variety of algorithms. The algorithm of choice depends, obviously, on its performance. Performance of su...
Confirming the Lanchestrian linear-logarithmic model of attrition
Hartley, D.S. III.
1990-12-01
This paper is the fourth in a series of reports on the breakthrough research in historical validation of attrition in conflict. Significant defense policy decisions, including weapons acquisition and arms reduction, are based in part on models of conflict. Most of these models are driven by their attrition algorithms, usually forms of the Lanchester square and linear laws. None of these algorithms have been validated. The results of this paper confirm the results of earlier papers, using a large database of historical results. The homogeneous linear-logarithmic Lanchestrian attrition model is validated to the extent possible with current initial and final force size data and is consistent with the Iwo Jima data. A particular differential linear-logarithmic model is described that fits the data very well. A version of Helmbold's victory predicting parameter is also confirmed, with an associated probability function. 37 refs., 73 figs., 68 tabs.
Non-Linear Finite Element Modeling of THUNDER Piezoelectric Actuators
Taleghani, Barmac K.; Campbell, Joel F.
1999-01-01
A NASTRAN non-linear finite element model has been developed for predicting the dome heights of THUNDER (THin Layer UNimorph Ferroelectric DrivER) piezoelectric actuators. To analytically validate the finite element model, a comparison was made with a non-linear plate solution using Von Karmen's approximation. A 500 volt input was used to examine the actuator deformation. The NASTRAN finite element model was also compared with experimental results. Four groups of specimens were fabricated and tested. Four different input voltages, which included 120, 160, 200, and 240 Vp-p with a 0 volts offset, were used for this comparison.
Linear mixed models a practical guide using statistical software
West, Brady T; Galecki, Andrzej T
2006-01-01
Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-navigate reference details the use of procedures for fitting LMMs in five popular statistical software packages: SAS, SPSS, Stata, R/S-plus, and HLM. The authors introduce basic theoretical concepts, present a heuristic approach to fitting LMMs based on bo
Forecasting Realized Volatility with Linear and Nonlinear Models
M.J. McAleer (Michael); M.C. Medeiros (Marcelo)
2009-01-01
textabstractIn this paper we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 indexes. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is comput
BRST symmetries in SU(3) linear sigma model
We study the BRST symmetries in the SU(3) linear sigma model which is constructed through the introduction of a novel matrix for the Goldstone boson fields satisfying geometrical constraints embedded in a SU(2) subgroup. To treat these constraints we exploit the improved Dirac quantization scheme. We also discuss phenomenological aspects in the mean field approach to this model. (orig.)
A random effects generalized linear model for reliability compositive evaluation
无
2009-01-01
This paper first proposes a random effects generalized linear model to evaluate the storage life of one kind of high reliable and small sample-sized products by combining multi-sources information of products coming from the same population but stored at different environments. The relevant algorithms are also provided. Simulation results manifest the soundness and effectiveness of the proposed model.
CONTRIBUTIONS TO THE FINITE ELEMENT MODELING OF LINEAR ULTRASONIC MOTORS
Oana CHIVU
2013-05-01
Full Text Available The present paper is concerned with the main modeling elements as produced by means of thefinite element method of linear ultrasonic motors. Hence, first the model is designed and then a modaland harmonic analysis are carried out in view of outlining the main outcomes
Optical linear algebra processors - Noise and error-source modeling
Casasent, D.; Ghosh, A.
1985-01-01
The modeling of system and component noise and error sources in optical linear algebra processors (OLAPs) are considered, with attention to the frequency-multiplexed OLAP. General expressions are obtained for the output produced as a function of various component errors and noise. A digital simulator for this model is discussed.
Supersparse Linear Integer Models for Predictive Scoring Systems
Ustun, Berk; Traca, Stefano; Rudin, Cynthia
2013-01-01
We introduce Supersparse Linear Integer Models (SLIM) as a tool to create scoring systems for binary classification. We derive theoretical bounds on the true risk of SLIM scoring systems, and present experimental results to show that SLIM scoring systems are accurate, sparse, and interpretable classification models.
Logical consistency and sum-constrained linear models
van Perlo -ten Kleij, Frederieke; Steerneman, A.G.M.; Koning, Ruud H.
2006-01-01
A topic that has received quite some attention in the seventies and eighties is logical consistency of sum-constrained linear models. Loosely defined, a sum-constrained model is logically consistent if the restrictions on the parameters and explanatory variables are such that the sum constraint is a
A Linearized Convective Overturning Model for Prediction of Thunderstorm Movement.
Marroquin, Adrian; Raymond, David J.
1982-01-01
A linearized model of convective overturning in shear for prediction of storm propagation is presented. Good correspondence between the model and observation is found for a number of case studies of real storms. Supercell storms, however, are an exception-the tendency to move to the right of the mean winds is not reproduced.
CONSISTENCY OF LS ESTIMATOR IN SIMPLE LINEAR EV REGRESSION MODELS
Liu Jixue; Chen Xiru
2005-01-01
Consistency of LS estimate of simple linear EV model is studied. It is shown that under some common assumptions of the model, both weak and strong consistency of the estimate are equivalent but it is not so for quadratic-mean consistency.
A Comprehensive X-Ray Absorption Model for Atomic Oxygen
Gorczyca, T. W.; Bautista, M. A.; Hasoglu, M. F.; Garcia, J.; Gatuzz, E.; Kaastra, J. S.; Kallman, T. R.; Manson, S. T.; Mendoza, C.; Raassen, A. J. J.; de Vries, C. P.; Zatsarinny, O.
2013-01-01
An analytical formula is developed to accurately represent the photoabsorption cross section of atomic Oxygen for all energies of interest in X-ray spectral modeling. In the vicinity of the K edge, a Rydberg series expression is used to fit R-matrix results, including important orbital relaxation effects, that accurately predict the absorption oscillator strengths below threshold and merge consistently and continuously to the above-threshold cross section. Further, minor adjustments are made to the threshold energies in order to reliably align the atomic Rydberg resonances after consideration of both experimental and observed line positions. At energies far below or above the K-edge region, the formulation is based on both outer- and inner-shell direct photoionization, including significant shake-up and shake-off processes that result in photoionization-excitation and double-photoionization contributions to the total cross section. The ultimate purpose for developing a definitive model for oxygen absorption is to resolve standing discrepancies between the astronomically observed and laboratory-measured line positions, and between the inferred atomic and molecular oxygen abundances in the interstellar medium from XSTAR and SPEX spectral models.
Holst, René; Jørgensen, Bent
2015-01-01
The paper proposes a versatile class of multiplicative generalized linear longitudinal mixed models (GLLMM) with additive dispersion components, based on explicit modelling of the covariance structure. The class incorporates a longitudinal structure into the random effects models and retains a ma...... multidimensional integral of the conventional GLMM likelihood and allows an extension of the robust empirical sandwich estimator for use with both association and regression parameters. The method is applied to a set of otholit data, used for age determination of fish.......The paper proposes a versatile class of multiplicative generalized linear longitudinal mixed models (GLLMM) with additive dispersion components, based on explicit modelling of the covariance structure. The class incorporates a longitudinal structure into the random effects models and retains a...... marginal as well as a conditional interpretation. The estimation procedure is based on a computationally efficient quasi-score method for the regression parameters combined with a REML-like bias-corrected Pearson estimating function for the dispersion and correlation parameters. This avoids the...
Daily Reference Evapotranspiration Estimation using Linear Regression and ANN Models
Mallikarjuna, P.; Jyothy, S. A.; Sekhar Reddy, K. C.
2012-12-01
The present study investigates the applicability of linear regression and ANN models for estimating daily reference evapotranspiration (ET0) at Tirupati, Nellore, Rajahmundry, Anakapalli and Rajendranagar regions of Andhra Pradesh. The climatic parameters influencing daily ET0 were identified through multiple and partial correlation analysis. The daily temperature, wind velocity, relative humidity and sunshine hours mostly influenced the study area in the daily ET0 estimation. Linear regression models in terms of the climatic parameters influencing the region and, optimal neural network architectures considering these influencing climatic parameters as input parameters were developed. The models' performance in the estimation of ET0 was evaluated with that estimated by FAO-56 Penman-Montieth method. The regression models showed a satisfactory performance in the daily ET0 estimation for the regions selected for the present study. The optimal ANN (4,4,1) models, however, consistently showed an improved performance over regression models.
Modelling and measurement of a moving magnet linear compressor performance
A novel moving magnet linear compressor with clearance seals and flexure bearings has been designed and constructed. It is suitable for a refrigeration system with a compact heat exchanger, such as would be needed for CPU cooling. The performance of the compressor has been experimentally evaluated with nitrogen and a mathematical model has been developed to evaluate the performance of the linear compressor. The results from the compressor model and the measurements have been compared in terms of cylinder pressure, the ‘P–V’ loop, stroke, mass flow rate and shaft power. The cylinder pressure was not measured directly but was derived from the compressor dynamics and the motor magnetic force characteristics. The comparisons indicate that the compressor model is well validated and can be used to study the performance of this type of compressor, to help with design optimization and the identification of key parameters affecting the system transients. The electrical and thermodynamic losses were also investigated, particularly for the design point (stroke of 13 mm and pressure ratio of 3.0), since a full understanding of these can lead to an increase in compressor efficiency. - Highlights: • Model predictions of the performance of a novel moving magnet linear compressor. • Prototype linear compressor performance measurements using nitrogen. • Reconstruction of P–V loops using a model of the dynamics and electromagnetics. • Close agreement between the model and measurements for the P–V loops. • The design point motor efficiency was 74%, with potential improvements identified
Regularization Paths for Generalized Linear Models via Coordinate Descent
Jerome Friedman
2010-02-01
Full Text Available We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multi- nomial regression problems while the penalties include ℓ1 (the lasso, ℓ2 (ridge regression and mixtures of the two (the elastic net. The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In comparative timings we find that the new algorithms are considerably faster than competing methods.
A Mathematical Theory of the Gauged Linear Sigma Model
Fan, Huijun; Ruan, Yongbin
2015-01-01
We construct a rigorous mathematical theory of Witten's Gauged Linear Sigma Model (GLSM). Our theory applies to a wide range of examples, including many cases with non-Abelian gauge group. Both the Gromov-Witten theory of a Calabi-Yau complete intersection X and the Landau-Ginzburg dual (FJRW-theory) of X can be expressed as gauged linear sigma models. Furthermore, the Landau-Ginzburg/Calabi-Yau correspondence can be interpreted as a variation of the moment map or a deformation of GIT in the GLSM. This paper focuses primarily on the algebraic theory, while a companion article will treat the analytic theory.
A variational formulation for linear models in coupled dynamic thermoelasticity
A variational formulation for linear models in coupled dynamic thermoelasticity which quite naturally motivates the design of a numerical scheme for the problem, is studied. When linked to regularization or penalization techniques, this algorithm may be applied to more general models, namely, the ones that consider non-linear constraints associated to variational inequalities. The basic postulates of Mechanics and Thermodynamics as well as some well-known mathematical techniques are described. A thorough description of the algorithm implementation with the finite-element method is also provided. Proofs for existence and uniqueness of solutions and for convergence of the approximations are presented, and some numerical results are exhibited. (Author)
Categorical Models for a Semantically Linear Lambda-calculus
Marco Gaboardi; Mauro Piccolo
2010-01-01
This paper is about a categorical approach to model a very simple Semantically Linear lambda calculus, named Sll-calculus. This is a core calculus underlying the programming language SlPCF. In particular, in this work, we introduce the notion of Sll-Category, which is able to describe a very large class of sound models of Sll-calculus. Sll-Category extends in the natural way Benton, Bierman, Hyland and de Paiva's Linear Category, in order to soundly interpret all the constructs of Sll-calculu...
Precise Asymptotics of Error Variance Estimator in Partially Linear Models
Shao-jun Guo; Min Chen; Feng Liu
2008-01-01
In this paper, we focus our attention on the precise asymptoties of error variance estimator in partially linear regression models, yi = xTi β + g(ti) +εi, 1 ≤i≤n, {εi,i = 1,... ,n } are i.i.d random errors with mean 0 and positive finite variance q2. Following the ideas of Allan Gut and Aurel Spataru[7,8] and Zhang[21],on precise asymptotics in the Baum-Katz and Davis laws of large numbers and precise rate in laws of the iterated logarithm, respectively, and subject to some regular conditions, we obtain the corresponding results in partially linear regression models.
Modeling the diffusion/absorption response of a nanopore coated microporous silicon interface
Baker, C.; Laminack, W.; Gole, J. L.
2016-03-01
We outline a modeling study of an extrinsic semiconductor interface formed from the interaction of nanostructured metal oxide decorated porous silicon and used for sensing gas phase analytes. We consider simple conductometric sensors that operate at room temperature and atmospheric pressure. Nanostructured metal oxide deposition provides a matrix of responses to various analytes, facilitating the extraction of ambient gas concentrations from sensor responses. The sensors are simulated in four stages with an emphasis to the continual improvement of the modeling effort. Stage 1 focuses solely on the diffusion mechanics of an analyte gas into and out of a micro/nanoporous interface and the observed linear response at low concentrations. Stage 2 focuses on the non-linearity resulting primarily from the quenching of sensor response at higher concentrations and introduces an absorption response mechanism. Here, stage 3 demonstrates how the consideration of charge carrier density leads to the development of a new Fermi-distribution based response mechanism. Stage 4 establishes a combined absorption-Fermi-distribution response mechanism.
Forecasting Realized Volatility with Linear and Nonlinear Models
McAleer, Michael; Medeiros, Marcelo
2010-01-01
textabstractIn this paper we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 indexes. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high frequency intra-day returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analyzed in the paper.
Inference of High-dimensional Autoregressive Generalized Linear Models
Hall, Eric C.; Raskutti, Garvesh; Willett, Rebecca
2016-01-01
Vector autoregressive models characterize a variety of time series in which linear combinations of current and past observations can be used to accurately predict future observations. For instance, each element of an observation vector could correspond to a different node in a network, and the parameters of an autoregressive model would correspond to the impact of the network structure on the time series evolution. Often these models are used successfully in practice to learn the structure of...
Functional linear models for association analysis of quantitative traits.
Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao
2013-11-01
Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. PMID:24130119
Photosensitizer absorption coefficient modeling and necrosis prediction during Photodynamic Therapy.
Salas-García, Irene; Fanjul-Vélez, Félix; Arce-Diego, José Luis
2012-09-01
The development of accurate predictive models for Photodynamic Therapy (PDT) has emerged as a valuable tool to adjust the current therapy dosimetry to get an optimal treatment response, and definitely to establish new personal protocols. Several attempts have been made in this way, although the influence of the photosensitizer depletion on the optical parameters has not been taken into account so far. We present a first approach to predict the spatio-temporal variation of the photosensitizer absorption coefficient during PDT applied to dermatological diseases, taking into account the photobleaching of a topical photosensitizer. This permits us to obtain the photons density absorbed by the photosensitizer molecules as the treatment progresses and to determine necrosis maps to estimate the short term therapeutic effects in the target tissue. The model presented also takes into account an inhomogeneous initial photosensitizer distribution, light propagation in biological media and the evolution of the molecular concentrations of different components involved in the photochemical reactions. The obtained results allow to investigate how the photosensitizer depletion during the photochemical reactions affects light absorption by the photosensitizer molecules as the optical radiation propagates through the target tissue, and estimate the necrotic tumor area progression under different treatment conditions. PMID:22704663
Neighborhood approximations for non-linear voter models
Schweitzer, Frank
2016-01-01
Non-linear voter models assume that the opinion of an agent depends on the opinions of its neighbors in a non-linear manner. This allows for voting rules different from majority voting. While the linear voter model is known to reach consensus, non-linear voter models can result in the coexistence of opposite opinions. Our aim is to derive approximations to correctly predict the time dependent dynamics, or at least the asymptotic outcome, of such local interactions. Emphasis is on a probabilistic approach to decompose the opinion distribution in a second-order neighborhood into lower-order probability distributions. This is compared with an analytic pair approximation for the expected value of the global fraction of opinions and a mean-field approximation. Our reference case are averaged stochastic simulations of a one-dimensional cellular automaton. We find that the probabilistic second-order approach captures the dynamics of the reference case very well for different non-linearities, i.e for both majority an...
Ahmed, S. Jbara; Zulkafli, Othaman; M, A. Saeed
2016-05-01
Based on the Schrödinger equation for envelope function in the effective mass approximation, linear and nonlinear optical absorption coefficients in a multi-subband lens quantum dot are investigated. The effects of quantum dot size on the interband and intraband transitions energy are also analyzed. The finite element method is used to calculate the eigenvalues and eigenfunctions. Strain and In-mole-fraction effects are also studied, and the results reveal that with the decrease of the In-mole fraction, the amplitudes of linear and nonlinear absorption coefficients increase. The present computed results show that the absorption coefficients of transitions between the first excited states are stronger than those of the ground states. In addition, it has been found that the quantum dot size affects the amplitudes and peak positions of linear and nonlinear absorption coefficients while the incident optical intensity strongly affects the nonlinear absorption coefficients. Project supported by the Ministry of Higher Education and Scientific Research in Iraq, Ibnu Sina Institute and Physics Department of Universiti Teknologi Malaysia (UTM RUG Vote No. 06-H14).
Multikernel linear mixed models for complex phenotype prediction.
Weissbrod, Omer; Geiger, Dan; Rosset, Saharon
2016-07-01
Linear mixed models (LMMs) and their extensions have recently become the method of choice in phenotype prediction for complex traits. However, LMM use to date has typically been limited by assuming simple genetic architectures. Here, we present multikernel linear mixed model (MKLMM), a predictive modeling framework that extends the standard LMM using multiple-kernel machine learning approaches. MKLMM can model genetic interactions and is particularly suitable for modeling complex local interactions between nearby variants. We additionally present MKLMM-Adapt, which automatically infers interaction types across multiple genomic regions. In an analysis of eight case-control data sets from the Wellcome Trust Case Control Consortium and more than a hundred mouse phenotypes, MKLMM-Adapt consistently outperforms competing methods in phenotype prediction. MKLMM is as computationally efficient as standard LMMs and does not require storage of genotypes, thus achieving state-of-the-art predictive power without compromising computational feasibility or genomic privacy. PMID:27302636
Evolution of linear perturbations in spherically symmetric dust models
February, Sean; Clarkson, Chris; Pollney, Denis
2013-01-01
We present a new numerical code to solve the master equations describing the evolution of linear perturbations in a spherically symmetric but inhomogeneous background. This code can be used to simulate several configurations of physical interest, such as relativistic corrections to structure formation, the lensing of gravitational waves and the evolution of perturbations in a cosmological void model. This paper focuses on the latter problem, i.e. structure formation in a Hubble scale void in the linear regime. This is considerably more complicated than linear perturbations of a homogeneous and isotropic background because the inhomogeneous background leads to coupling between density perturbations and rotational modes of the spacetime geometry, as well as gravitational waves. Previous analyses of this problem ignored this coupling in the hope that the approximation does not affect the overall dynamics of structure formation in such models. We show that for a giga-parsec void, the evolution of the density cont...
Y. Y. Lee
2014-01-01
Full Text Available This study includes the first work about the absorption of a panel absorber under the effects of microperforation, air pumping, and linear and nonlinear vibrations. In practice, thin perforated panel absorber is backed by a flexible wall to enhance the acoustic performance within the room. The panel is easily excited to vibrate nonlinearly and the wall can vibrate linearly. However, the assumptions of linear panel vibration and no wall vibration are adopted in many research works. The development of the absorption formula is based on the classical approach and the electroacoustic analogy, in which the impedances of microperforation, air pumping, and linear and nonlinear vibrations are in parallel and connected to that of the air cavity in series. Unlike those finite element, numerical integration, and multiscale solution methods and so forth, the analytic formula to calculate the absorption of a panel absorber does not require heavy computation effort and is suitable for engineering calculation purpose. The theoretical result obtained from the proposed method shows reasonable agreement with that from a previous numerical integration method. It can be concluded that the overall absorption bandwidth of a panel absorber with an appropriate configuration can be optimized and widened by making use of the positive effects of microperforation, air pumping, and panel vibration.