A Duality Result for the Generalized Erlang Risk Model
Directory of Open Access Journals (Sweden)
Lanpeng Ji
2014-11-01
Full Text Available In this article, we consider the generalized Erlang risk model and its dual model. By using a conditional measure-preserving correspondence between the two models, we derive an identity for two interesting conditional probabilities. Applications to the discounted joint density of the surplus prior to ruin and the deficit at ruin are also discussed.
Inhibition in speed and concentration tests: The Poisson inhibition model
Smit, J.C.; Ven, A.H.G.S. van der
1995-01-01
A new model is presented to account for the reaction time fluctuations in concentration tests. The model is a natural generalization of an earlier model, the so-called Poisson-Erlang model, published by Pieters & van der Ven (1982). First, a description is given of the type of tasks for which the
A large deviations approach to the transient of the Erlang loss model
Mandjes, M.R.H.; Ridder, Annemarie
2001-01-01
This paper deals with the transient behavior of the Erlang loss model. After scaling both arrival rate and number of trunks, an asymptotic analysis of the blocking probability is given. Apart from that, the most likely path to blocking is given. Compared to Shwartz and Weiss [Large Deviations for
Zero-truncated negative binomial - Erlang distribution
Bodhisuwan, Winai; Pudprommarat, Chookait; Bodhisuwan, Rujira; Saothayanun, Luckhana
2017-11-01
The zero-truncated negative binomial-Erlang distribution is introduced. It is developed from negative binomial-Erlang distribution. In this work, the probability mass function is derived and some properties are included. The parameters of the zero-truncated negative binomial-Erlang distribution are estimated by using the maximum likelihood estimation. Finally, the proposed distribution is applied to real data, the number of methamphetamine in the Bangkok, Thailand. Based on the results, it shows that the zero-truncated negative binomial-Erlang distribution provided a better fit than the zero-truncated Poisson, zero-truncated negative binomial, zero-truncated generalized negative-binomial and zero-truncated Poisson-Lindley distributions for this data.
Modeling Erlang's Ideal Grading with Multirate BPP Traffic
Directory of Open Access Journals (Sweden)
Mariusz Glabowski
2012-01-01
Full Text Available This paper presents a complete methodology for modeling gradings (also called non-full-availability groups servicing single-service and multi-service traffic streams. The methodology worked out by the authors makes it possible to determine traffic characteristics of various types of gradings with state-dependent call arrival processes, including a new proposed structure of the Erlang’s Ideal Grading with the multirate links. The elaborated models of the gradings can be used for modeling different systems of modern networks, for example, the radio interfaces of the UMTS system, switching networks carrying a mixture of different multirate traffic streams, and video-on-demand systems. The results of the analytical calculations are compared with the results of the simulation data for selected gradings, which confirm high accuracy of the proposed methodology.
Autocoding State Machine in Erlang
DEFF Research Database (Denmark)
Guo, Yu; Hoffman, Torben; Gunder, Nicholas
2008-01-01
This paper presents an autocoding tool suit, which supports development of state machine in a model-driven fashion, where models are central to all phases of the development process. The tool suit, which is built on the Eclipse platform, provides facilities for the graphical specification...... of a state machine model. Once the state machine is specified, it is used as input to a code generation engine that generates source code in Erlang....
Directory of Open Access Journals (Sweden)
A. D. Khomonenko
2016-07-01
Full Text Available Subject of Research.Software reliability and test planning models are studied taking into account the probabilistic nature of error detection and discovering. Modeling of software testing enables to plan the resources and final quality at early stages of project execution. Methods. Two dynamic models of processes (strategies are suggested for software testing, using error detection probability for each software module. The Erlang distribution is used for arbitrary distribution approximation of fault resolution duration. The exponential distribution is used for approximation of fault resolution discovering. For each strategy, modified labeled graphs are built, along with differential equation systems and their numerical solutions. The latter makes it possible to compute probabilistic characteristics of the test processes and states: probability states, distribution functions for fault detection and elimination, mathematical expectations of random variables, amount of detected or fixed errors. Evaluation of Results. Probabilistic characteristics for software development projects were calculated using suggested models. The strategies have been compared by their quality indexes. Required debugging time to achieve the specified quality goals was calculated. The calculation results are used for time and resources planning for new projects. Practical Relevance. The proposed models give the possibility to use the reliability estimates for each individual module. The Erlang approximation removes restrictions on the use of arbitrary time distribution for fault resolution duration. It improves the accuracy of software test process modeling and helps to take into account the viability (power of the tests. With the use of these models we can search for ways to improve software reliability by generating tests which detect errors with the highest probability.
A Seemingly Unrelated Poisson Regression Model
King, Gary
1989-01-01
This article introduces a new estimator for the analysis of two contemporaneously correlated endogenous event count variables. This seemingly unrelated Poisson regression model (SUPREME) estimator combines the efficiencies created by single equation Poisson regression model estimators and insights from "seemingly unrelated" linear regression models.
On multi-rate Erlang-B computations
DEFF Research Database (Denmark)
Iversen, Villy Bæk; Nilsson, A.A.; Perry, M.
1999-01-01
-rate Erlang-B model is often used even for today's new networks. A primary reason for this is the existence of methods to compute blocking probabilities and their derivatives that are simple, fast, and stable. With this paper, we provide an improved, and better, way of computing multi-rate Erlang-B blocking...... probabilities and their derivatives. Since the improvements are also simple, fast, direct, and stable, optimization and engineering methods based on a single-rate Erlang-B model can now be easily extended to emerging multimedia networks....
DEFF Research Database (Denmark)
Iversen, Villy Bæk
2012-01-01
This paper presents a robust and efficient algorithm for evaluating multi-service multi-rate queueing systems, including finite buffer systems and loss systems. Vint Cerf listed in 2007 seven research problems concerning the Internet. This paper responds to the second problem: an Internet Erlang...... is O{N · k} where N number of services, and k is the total number of servers and buffers in basic bandwidth units. The memory requirement is O{N · d} where d is the maximum requested bandwidth in basic bandwidth units....
Evaluating the double Poisson generalized linear model.
Zou, Yaotian; Geedipally, Srinivas Reddy; Lord, Dominique
2013-10-01
The objectives of this study are to: (1) examine the applicability of the double Poisson (DP) generalized linear model (GLM) for analyzing motor vehicle crash data characterized by over- and under-dispersion and (2) compare the performance of the DP GLM with the Conway-Maxwell-Poisson (COM-Poisson) GLM in terms of goodness-of-fit and theoretical soundness. The DP distribution has seldom been investigated and applied since its first introduction two decades ago. The hurdle for applying the DP is related to its normalizing constant (or multiplicative constant) which is not available in closed form. This study proposed a new method to approximate the normalizing constant of the DP with high accuracy and reliability. The DP GLM and COM-Poisson GLM were developed using two observed over-dispersed datasets and one observed under-dispersed dataset. The modeling results indicate that the DP GLM with its normalizing constant approximated by the new method can handle crash data characterized by over- and under-dispersion. Its performance is comparable to the COM-Poisson GLM in terms of goodness-of-fit (GOF), although COM-Poisson GLM provides a slightly better fit. For the over-dispersed data, the DP GLM performs similar to the NB GLM. Considering the fact that the DP GLM can be easily estimated with inexpensive computation and that it is simpler to interpret coefficients, it offers a flexible and efficient alternative for researchers to model count data. Copyright © 2013 Elsevier Ltd. All rights reserved.
Affine Poisson Groups and WZW Model
Directory of Open Access Journals (Sweden)
Ctirad Klimcík
2008-01-01
Full Text Available We give a detailed description of a dynamical system which enjoys a Poisson-Lie symmetry with two non-isomorphic dual groups. The system is obtained by taking the q → ∞ limit of the q-deformed WZW model and the understanding of its symmetry structure results in uncovering an interesting duality of its exchange relations.
A Reliable Instant Messenger in Erlang: Design and Evaluation
Hernandez, Mario Moro; Chechina, Natalia; Trinder, Phil
2015-01-01
This document describes the design and evaluation of two Erlang-based instant messenger systems using Distributed Erlang (D-Erlang) and Scalable Distributed Erlang (SD-Erlang). The purpose of these systems is to serve as real-world benchmarks to test the performance of the SD Erlang library.
Fitting mixtures of Erlangs to censored and truncated data using the EM algorithm
Verbelen, R.; Gong, L.; Antonio, K.; Badescu, A.; Lin, S.
2015-01-01
We discuss how to fit mixtures of Erlangs to censored and truncated data by iteratively using the EM algorithm. Mixtures of Erlangs form a very versatile, yet analytically tractable, class of distributions making them suitable for loss modeling purposes. The effectiveness of the proposed algorithm
Directory of Open Access Journals (Sweden)
Moon Ho Lee
2008-01-01
Full Text Available A multiserver queueing model that does not have a buffer but has batch arrival of customers is considered. In contrast to the standard batch arrival, in which the entire batch arrives at the system during a single epoch, we assume that the customers of a batch (flow arrive individually in exponentially distributed times. The service time is exponentially distributed. Flows arrive according to a stationary Poisson arrival process. The flow size distribution is geometric. The number of flows that can be simultaneously admitted to the system is under control. The loss of any customer from an admitted flow, with a fixed probability, implies termination of the flow arrival. Analysis of the sojourn time and loss probability of an arbitrary flow is performed.
On multi-rate Erlang-B computations
DEFF Research Database (Denmark)
Iversen, Villy Bæk; Nilsson, A.A.; Perry, M.
1999-01-01
The single-rate Erlang-B model is and has been a cornerstone of numerous traffic engineering applications which involve the calculation and optimization of blocking probabilities. However, with the emerging integrated multimedia networks, one single traffic type is often inadequate. Yet the singl...
Erlang Capacity of Multi-class TDMA Systems with Adaptive Modulation and Coding
DEFF Research Database (Denmark)
Wang, Hua; Iversen, Villy Bæk
2008-01-01
conditions. In this paper, we evaluate the Erlang capacity of a TDMA system with AMC supporting voice and data traffics, by taking both the blocking and the outage probabilities into account. The analytical models for calculating the blocking and the outage probabilities are developed separately, and a joint......Erlang capacity is traditionally defined as the maximum value of offered traffic among different service classes that the system can support when the blocking probabilities at the call admission control (CAC) level do not exceed certain thresholds. That is valid when a fixed amount of bandwidth...... algorithm for determining the Erlang capacity of the system is proposed with some numerical examples....
Poisson Mixture Regression Models for Heart Disease Prediction
Erol, Hamza
2016-01-01
Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611
Modified Regression Correlation Coefficient for Poisson Regression Model
Kaengthong, Nattacha; Domthong, Uthumporn
2017-09-01
This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).
Approximations for the Erlang Loss Function
DEFF Research Database (Denmark)
Mejlbro, Leif
1998-01-01
Theoretically, at least three formulae are needed for arbitrarily good approximates of the Erlang Loss Function. In the paper, for convenience five formulae are presented guaranteeing a relative error <1E-2, and methods are indicated for improving this bound.......Theoretically, at least three formulae are needed for arbitrarily good approximates of the Erlang Loss Function. In the paper, for convenience five formulae are presented guaranteeing a relative error
Approximation of ruin probabilities via Erlangized scale mixtures
DEFF Research Database (Denmark)
Peralta, Oscar; Rojas-Nandayapa, Leonardo; Xie, Wangyue
2018-01-01
In this paper, we extend an existing scheme for numerically calculating the probability of ruin of a classical Cramér–Lundbergreserve process having absolutely continuous but otherwise general claim size distributions. We employ a dense class of distributions that we denominate Erlangized scale...... a simple methodology for constructing a sequence of distributions having the form Π⋆G with the purpose of approximating the integrated tail distribution of the claim sizes. Then we adapt a recent result which delivers an explicit expression for the probability of ruin in the case that the claim size...... distribution is modeled as an Erlangized scale mixture. We provide simplified expressions for the approximation of the probability of ruin and construct explicit bounds for the error of approximation. We complement our results with a classical example where the claim sizes are heavy-tailed....
Multivariate mixtures of Erlangs for density estimation under censoring
Verbelen, R.; Antonio, K.; Claeskens, G.
2016-01-01
Multivariate mixtures of Erlang distributions form a versatile, yet analytically tractable, class of distributions making them suitable for multivariate density estimation. We present a flexible and effective fitting procedure for multivariate mixtures of Erlangs, which iteratively uses the EM
Markov modulated Poisson process models incorporating covariates for rainfall intensity.
Thayakaran, R; Ramesh, N I
2013-01-01
Time series of rainfall bucket tip times at the Beaufort Park station, Bracknell, in the UK are modelled by a class of Markov modulated Poisson processes (MMPP) which may be thought of as a generalization of the Poisson process. Our main focus in this paper is to investigate the effects of including covariate information into the MMPP model framework on statistical properties. In particular, we look at three types of time-varying covariates namely temperature, sea level pressure, and relative humidity that are thought to be affecting the rainfall arrival process. Maximum likelihood estimation is used to obtain the parameter estimates, and likelihood ratio tests are employed in model comparison. Simulated data from the fitted model are used to make statistical inferences about the accumulated rainfall in the discrete time interval. Variability of the daily Poisson arrival rates is studied.
Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)
DEFF Research Database (Denmark)
Agosto, Arianna; Cavaliere, Guiseppe; Kristensen, Dennis
We develop a class of Poisson autoregressive models with additional covariates (PARX) that can be used to model and forecast time series of counts. We establish the time series properties of the models, including conditions for stationarity and existence of moments. These results are in turn used...
Poisson-generalized gamma empirical Bayes model for disease ...
African Journals Online (AJOL)
In spatial disease mapping, the use of Bayesian models of estimation technique is becoming popular for smoothing relative risks estimates for disease mapping. The most common Bayesian conjugate model for disease mapping is the Poisson-Gamma Model (PG). To explore further the activity of smoothing of relative risk ...
Double generalized linear compound poisson models to insurance claims data
DEFF Research Database (Denmark)
Andersen, Daniel Arnfeldt; Bonat, Wagner Hugo
2017-01-01
This paper describes the specification, estimation and comparison of double generalized linear compound Poisson models based on the likelihood paradigm. The models are motivated by insurance applications, where the distribution of the response variable is composed by a degenerate distribution...... in a finite sample framework. The simulation studies are also used to validate the fitting algorithms and check the computational implementation. Furthermore, we investigate the impact of an unsuitable choice for the response variable distribution on both mean and dispersion parameter estimates. We provide R...... implementation and illustrate the application of double generalized linear compound Poisson models using a data set about car insurances....
Development of an Erlang System Adaopted to Embedded Devices
Andersson, Fredrik; Bergström, Fabian
2011-01-01
Erlang is a powerful and robust language for writing massively parallel and distributed applications. With the introduction of multi-core ARM processors, the embedded market will be looking for ways of taking advantage of the newfound opportunities for parallelism. To support the development of embedded applications using Erlang we want to provide Erlang and Embedded developers with a run-time system suited for embedded devices. We have managed to shrink the disk size of the Erlang runtime sy...
The coupling of Poisson sigma models to topological backgrounds
Energy Technology Data Exchange (ETDEWEB)
Rosa, Dario [School of Physics, Korea Institute for Advanced Study,Seoul 02455 (Korea, Republic of)
2016-12-13
We extend the coupling to the topological backgrounds, recently worked out for the 2-dimensional BF-model, to the most general Poisson sigma models. The coupling involves the choice of a Casimir function on the target manifold and modifies the BRST transformations. This in turn induces a change in the BRST cohomology of the resulting theory. The observables of the coupled theory are analyzed and their geometrical interpretation is given. We finally couple the theory to 2-dimensional topological gravity: this is the first step to study a topological string theory in propagation on a Poisson manifold. As an application, we show that the gauge-fixed vectorial supersymmetry of the Poisson sigma models has a natural explanation in terms of the theory coupled to topological gravity.
Poisson sigma model with branes and hyperelliptic Riemann surfaces
International Nuclear Information System (INIS)
Ferrario, Andrea
2008-01-01
We derive the explicit form of the superpropagators in the presence of general boundary conditions (coisotropic branes) for the Poisson sigma model. This generalizes the results presented by Cattaneo and Felder [''A path integral approach to the Kontsevich quantization formula,'' Commun. Math. Phys. 212, 591 (2000)] and Cattaneo and Felder ['Coisotropic submanifolds in Poisson geometry and branes in the Poisson sigma model', Lett. Math. Phys. 69, 157 (2004)] for Kontsevich's angle function [Kontsevich, M., 'Deformation quantization of Poisson manifolds I', e-print arXiv:hep.th/0101170] used in the deformation quantization program of Poisson manifolds. The relevant superpropagators for n branes are defined as gauge fixed homotopy operators of a complex of differential forms on n sided polygons P n with particular ''alternating'' boundary conditions. In the presence of more than three branes we use first order Riemann theta functions with odd singular characteristics on the Jacobian variety of a hyperelliptic Riemann surface (canonical setting). In genus g the superpropagators present g zero mode contributions
An application of the Autoregressive Conditional Poisson (ACP) model
CSIR Research Space (South Africa)
Holloway, Jennifer P
2010-11-01
Full Text Available When modelling count data that comes in the form of a time series, the static Poisson regression and standard time series models are often not appropriate. A current study therefore involves the evaluation of several observation-driven and parameter...
Wide-area traffic: The failure of Poisson modeling
Energy Technology Data Exchange (ETDEWEB)
Paxson, V.; Floyd, S.
1994-08-01
Network arrivals are often modeled as Poisson processes for analytic simplicity, even though a number of traffic studies have shown that packet interarrivals are not exponentially distributed. The authors evaluate 21 wide-area traces, investigating a number of wide-area TCP arrival processes (session and connection arrivals, FTPDATA connection arrivals within FTP sessions, and TELNET packet arrivals) to determine the error introduced by modeling them using Poisson processes. The authors find that user-initiated TCP session arrivals, such as remote-login and file-transfer, are well-modeled as Poisson processes with fixed hourly rates, but that other connection arrivals deviate considerably from Poisson; that modeling TELNET packet interarrivals as exponential grievously underestimates the burstiness of TELNET traffic, but using the empirical Tcplib[DJCME92] interarrivals preserves burstiness over many time scales; and that FTPDATA connection arrivals within FTP sessions come bunched into ``connection bursts``, the largest of which are so large that they completely dominate FTPDATA traffic. Finally, they offer some preliminary results regarding how the findings relate to the possible self-similarity of wide-area traffic.
2D sigma models and differential Poisson algebras
Energy Technology Data Exchange (ETDEWEB)
Arias, Cesar [Departamento de Ciencias Físicas, Universidad Andres Bello,Republica 220, Santiago (Chile); Boulanger, Nicolas [Service de Mécanique et Gravitation, Université de Mons - UMONS,20 Place du Parc, 7000 Mons (Belgium); Laboratoire de Mathématiques et Physique Théorique,Unité Mixte de Recherche 7350 du CNRS, Fédération de Recherche 2964 Denis Poisson,Université François Rabelais, Parc de Grandmont, 37200 Tours (France); Sundell, Per [Departamento de Ciencias Físicas, Universidad Andres Bello,Republica 220, Santiago (Chile); Torres-Gomez, Alexander [Departamento de Ciencias Físicas, Universidad Andres Bello,Republica 220, Santiago (Chile); Instituto de Ciencias Físicas y Matemáticas, Universidad Austral de Chile-UACh,Valdivia (Chile)
2015-08-18
We construct a two-dimensional topological sigma model whose target space is endowed with a Poisson algebra for differential forms. The model consists of an equal number of bosonic and fermionic fields of worldsheet form degrees zero and one. The action is built using exterior products and derivatives, without any reference to a worldsheet metric, and is of the covariant Hamiltonian form. The equations of motion define a universally Cartan integrable system. In addition to gauge symmetries, the model has one rigid nilpotent supersymmetry corresponding to the target space de Rham operator. The rigid and local symmetries of the action, respectively, are equivalent to the Poisson bracket being compatible with the de Rham operator and obeying graded Jacobi identities. We propose that perturbative quantization of the model yields a covariantized differential star product algebra of Kontsevich type. We comment on the resemblance to the topological A model.
A hybrid sampler for Poisson-Kingman mixture models
Lomeli, M.; Favaro, S.; Teh, Y. W.
2015-01-01
This paper concerns the introduction of a new Markov Chain Monte Carlo scheme for posterior sampling in Bayesian nonparametric mixture models with priors that belong to the general Poisson-Kingman class. We present a novel compact way of representing the infinite dimensional component of the model such that while explicitly representing this infinite component it has less memory and storage requirements than previous MCMC schemes. We describe comparative simulation results demonstrating the e...
Erlang-Based Sensor Network Management For Heterogeneous Devices
Directory of Open Access Journals (Sweden)
Michal Niec
2012-01-01
Full Text Available The paper describes a system designed to manage and collect data from the network of heterogeneous sensors. It was implemented using Erlang OTP and CouchDB for maximum fault tolerance, scalability and ease of deployment. It is resistant to poor network quality, shows high tolerance for software errors and power failures, operates on ﬂexible data model. Additionally, it is available to users through an Web application, which shows just how easy it is to use the server HTTP API to communicate with it. The whole platform was implemented and tested on variety of devices like PC, Mac, ARM-based embedded devices and Android tablets.
modelling of queuing process at airport check-in system: a case ...
African Journals Online (AJOL)
HOD
memoryless) process described by Poisson distribution. Service times are independently and identically distributed or exponentially distributed random variables; the process is expressed by Erlange model [17, 19 - 21]. Queuing models are described using probability distribution of inter-arrivals and service times, number.
Collision prediction models using multivariate Poisson-lognormal regression.
El-Basyouny, Karim; Sayed, Tarek
2009-07-01
This paper advocates the use of multivariate Poisson-lognormal (MVPLN) regression to develop models for collision count data. The MVPLN approach presents an opportunity to incorporate the correlations across collision severity levels and their influence on safety analyses. The paper introduces a new multivariate hazardous location identification technique, which generalizes the univariate posterior probability of excess that has been commonly proposed and applied in the literature. In addition, the paper presents an alternative approach for quantifying the effect of the multivariate structure on the precision of expected collision frequency. The MVPLN approach is compared with the independent (separate) univariate Poisson-lognormal (PLN) models with respect to model inference, goodness-of-fit, identification of hot spots and precision of expected collision frequency. The MVPLN is modeled using the WinBUGS platform which facilitates computation of posterior distributions as well as providing a goodness-of-fit measure for model comparisons. The results indicate that the estimates of the extra Poisson variation parameters were considerably smaller under MVPLN leading to higher precision. The improvement in precision is due mainly to the fact that MVPLN accounts for the correlation between the latent variables representing property damage only (PDO) and injuries plus fatalities (I+F). This correlation was estimated at 0.758, which is highly significant, suggesting that higher PDO rates are associated with higher I+F rates, as the collision likelihood for both types is likely to rise due to similar deficiencies in roadway design and/or other unobserved factors. In terms of goodness-of-fit, the MVPLN model provided a superior fit than the independent univariate models. The multivariate hazardous location identification results demonstrated that some hazardous locations could be overlooked if the analysis was restricted to the univariate models.
On population size estimators in the Poisson mixture model.
Mao, Chang Xuan; Yang, Nan; Zhong, Jinhua
2013-09-01
Estimating population sizes via capture-recapture experiments has enormous applications. The Poisson mixture model can be adopted for those applications with a single list in which individuals appear one or more times. We compare several nonparametric estimators, including the Chao estimator, the Zelterman estimator, two jackknife estimators and the bootstrap estimator. The target parameter of the Chao estimator is a lower bound of the population size. Those of the other four estimators are not lower bounds, and they may produce lower confidence limits for the population size with poor coverage probabilities. A simulation study is reported and two examples are investigated. © 2013, The International Biometric Society.
Numerical solution of dynamic equilibrium models under Poisson uncertainty
DEFF Research Database (Denmark)
Posch, Olaf; Trimborn, Timo
2013-01-01
We propose a simple and powerful numerical algorithm to compute the transition process in continuous-time dynamic equilibrium models with rare events. In this paper we transform the dynamic system of stochastic differential equations into a system of functional differential equations...... of the retarded type. We apply the Waveform Relaxation algorithm, i.e., we provide a guess of the policy function and solve the resulting system of (deterministic) ordinary differential equations by standard techniques. For parametric restrictions, analytical solutions to the stochastic growth model and a novel...... solution to Lucas' endogenous growth model under Poisson uncertainty are used to compute the exact numerical error. We show how (potential) catastrophic events such as rare natural disasters substantially affect the economic decisions of households....
Polyelectrolyte Microcapsules: Ion Distributions from a Poisson-Boltzmann Model
Tang, Qiyun; Denton, Alan R.; Rozairo, Damith; Croll, Andrew B.
2014-03-01
Recent experiments have shown that polystyrene-polyacrylic-acid-polystyrene (PS-PAA-PS) triblock copolymers in a solvent mixture of water and toluene can self-assemble into spherical microcapsules. Suspended in water, the microcapsules have a toluene core surrounded by an elastomer triblock shell. The longer, hydrophilic PAA blocks remain near the outer surface of the shell, becoming charged through dissociation of OH functional groups in water, while the shorter, hydrophobic PS blocks form a networked (glass or gel) structure. Within a mean-field Poisson-Boltzmann theory, we model these polyelectrolyte microcapsules as spherical charged shells, assuming different dielectric constants inside and outside the capsule. By numerically solving the nonlinear Poisson-Boltzmann equation, we calculate the radial distribution of anions and cations and the osmotic pressure within the shell as a function of salt concentration. Our predictions, which can be tested by comparison with experiments, may guide the design of microcapsules for practical applications, such as drug delivery. This work was supported by the National Science Foundation under Grant No. DMR-1106331.
Modeling the number of car theft using Poisson regression
Zulkifli, Malina; Ling, Agnes Beh Yen; Kasim, Maznah Mat; Ismail, Noriszura
2016-10-01
Regression analysis is the most popular statistical methods used to express the relationship between the variables of response with the covariates. The aim of this paper is to evaluate the factors that influence the number of car theft using Poisson regression model. This paper will focus on the number of car thefts that occurred in districts in Peninsular Malaysia. There are two groups of factor that have been considered, namely district descriptive factors and socio and demographic factors. The result of the study showed that Bumiputera composition, Chinese composition, Other ethnic composition, foreign migration, number of residence with the age between 25 to 64, number of employed person and number of unemployed person are the most influence factors that affect the car theft cases. These information are very useful for the law enforcement department, insurance company and car owners in order to reduce and limiting the car theft cases in Peninsular Malaysia.
Estimation of a Non-homogeneous Poisson Model: An Empirical ...
African Journals Online (AJOL)
This article aims at applying the Nonhomogeneous Poisson process to trends of economic development. For this purpose, a modified Nonhomogeneous Poisson process is derived when the intensity rate is considered as a solution of stochastic differential equation which satisfies the geometric Brownian motion. The mean ...
Electroneutral models for dynamic Poisson-Nernst-Planck systems
Song, Zilong; Cao, Xiulei; Huang, Huaxiong
2018-01-01
The Poisson-Nernst-Planck (PNP) system is a standard model for describing ion transport. In many applications, e.g., ions in biological tissues, the presence of thin boundary layers poses both modeling and computational challenges. In this paper, we derive simplified electroneutral (EN) models where the thin boundary layers are replaced by effective boundary conditions. There are two major advantages of EN models. First, it is much cheaper to solve them numerically. Second, EN models are easier to deal with compared to the original PNP system; therefore, it would also be easier to derive macroscopic models for cellular structures using EN models. Even though the approach used here is applicable to higher-dimensional cases, this paper mainly focuses on the one-dimensional system, including the general multi-ion case. Using systematic asymptotic analysis, we derive a variety of effective boundary conditions directly applicable to the EN system for the bulk region. This EN system can be solved directly and efficiently without computing the solution in the boundary layer. The derivation is based on matched asymptotics, and the key idea is to bring back higher-order contributions into the effective boundary conditions. For Dirichlet boundary conditions, the higher-order terms can be neglected and the classical results (continuity of electrochemical potential) are recovered. For flux boundary conditions, higher-order terms account for the accumulation of ions in boundary layer and neglecting them leads to physically incorrect solutions. To validate the EN model, numerical computations are carried out for several examples. Our results show that solving the EN model is much more efficient than the original PNP system. Implemented with the Hodgkin-Huxley model, the computational time for solving the EN model is significantly reduced without sacrificing the accuracy of the solution due to the fact that it allows for relatively large mesh and time-step sizes.
An Erlang Implementation of Multiparty Session Actors
Directory of Open Access Journals (Sweden)
Simon Fowler
2016-08-01
Full Text Available By requiring co-ordination to take place using explicit message passing instead of relying on shared memory, actor-based programming languages have been shown to be effective tools for building reliable and fault-tolerant distributed systems. Although naturally communication-centric, communication patterns in actor-based applications remain informally specified, meaning that errors in communication are detected late, if at all. Multiparty session types are a formalism to describe, at a global level, the interactions between multiple communicating entities. This article describes the implementation of a prototype framework for monitoring Erlang/OTP gen_server applications against multiparty session types, showing how previous work on multiparty session actors can be adapted to a purely actor-based language, and how monitor violations and termination of session participants can be reported in line with the Erlang mantra of "let it fail". Finally, the framework is used to implement two case studies: an adaptation of a freely-available DNS server, and a chat server.
Comparing Multicomponent Erlang Distribution and Lévy Distribution of Particle Transverse Momentums
International Nuclear Information System (INIS)
Wei, Hua-Rong; Chen, Ya-Hui; Gao, Li-Na; Liu, Fu-Hu
2014-01-01
The transverse momentum spectrums of final-state products produced in nucleus-nucleus and proton-proton collisions at different center-of-mass energies are analyzed by using a multicomponent Erlang distribution and the Lévy distribution. The results calculated by the two models are found in most cases to be in agreement with experimental data from the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC). The multicomponent Erlang distribution that resulted from a multisource thermal model seems to give a better description as compared with the Lévy distribution. The temperature parameters of interacting system corresponding to different types of final-state products are obtained. Light particles correspond to a low temperature emission, and heavy particles correspond to a high temperature emission. Extracted temperature from central collisions is higher than that from peripheral collisions
Lord, Dominique; Geedipally, Srinivas Reddy; Guikema, Seth D
2010-08-01
The objective of this article is to evaluate the performance of the COM-Poisson GLM for analyzing crash data exhibiting underdispersion (when conditional on the mean). The COM-Poisson distribution, originally developed in 1962, has recently been reintroduced by statisticians for analyzing count data subjected to either over- or underdispersion. Over the last year, the COM-Poisson GLM has been evaluated in the context of crash data analysis and it has been shown that the model performs as well as the Poisson-gamma model for crash data exhibiting overdispersion. To accomplish the objective of this study, several COM-Poisson models were estimated using crash data collected at 162 railway-highway crossings in South Korea between 1998 and 2002. This data set has been shown to exhibit underdispersion when models linking crash data to various explanatory variables are estimated. The modeling results were compared to those produced from the Poisson and gamma probability models documented in a previous published study. The results of this research show that the COM-Poisson GLM can handle crash data when the modeling output shows signs of underdispersion. Finally, they also show that the model proposed in this study provides better statistical performance than the gamma probability and the traditional Poisson models, at least for this data set.
The Rasch Poisson counts model for incomplete data : An application of the EM algorithm
Jansen, G.G.H.
Rasch's Poisson counts model is a latent trait model for the situation in which K tests are administered to N examinees and the test score is a count [e.g., the repeated occurrence of some event, such as the number of items completed or the number of items answered (in)correctly]. The Rasch Poisson
Erlang Programming A Concurrent Approach to Software Development
Cesarini, Francesco
2009-01-01
This book offers you an in-depth explanation of Erlang, a programming language ideal for any situation where concurrency, fault-tolerance, and fast response is essential. You'll learn how to write complex concurrent programs in this language, regardless of your programming background or experience. Erlang Programming focuses on the language's syntax and semantics, and explains pattern matching, proper lists, recursion, debugging, networking, and concurrency, with exercises at the end of each chapter.
Characterizing the performance of the Conway-Maxwell Poisson generalized linear model.
Francis, Royce A; Geedipally, Srinivas Reddy; Guikema, Seth D; Dhavala, Soma Sekhar; Lord, Dominique; LaRocca, Sarah
2012-01-01
Count data are pervasive in many areas of risk analysis; deaths, adverse health outcomes, infrastructure system failures, and traffic accidents are all recorded as count events, for example. Risk analysts often wish to estimate the probability distribution for the number of discrete events as part of doing a risk assessment. Traditional count data regression models of the type often used in risk assessment for this problem suffer from limitations due to the assumed variance structure. A more flexible model based on the Conway-Maxwell Poisson (COM-Poisson) distribution was recently proposed, a model that has the potential to overcome the limitations of the traditional model. However, the statistical performance of this new model has not yet been fully characterized. This article assesses the performance of a maximum likelihood estimation method for fitting the COM-Poisson generalized linear model (GLM). The objectives of this article are to (1) characterize the parameter estimation accuracy of the MLE implementation of the COM-Poisson GLM, and (2) estimate the prediction accuracy of the COM-Poisson GLM using simulated data sets. The results of the study indicate that the COM-Poisson GLM is flexible enough to model under-, equi-, and overdispersed data sets with different sample mean values. The results also show that the COM-Poisson GLM yields accurate parameter estimates. The COM-Poisson GLM provides a promising and flexible approach for performing count data regression. © 2011 Society for Risk Analysis.
The Lie-Poisson structure of integrable classical non-linear sigma models
International Nuclear Information System (INIS)
Bordemann, M.; Forger, M.; Schaeper, U.; Laartz, J.
1993-01-01
The canonical structure of classical non-linear sigma models on Riemannian symmetric spaces, which constitute the most general class of classical non-linear sigma models known to be integrable, is shown to be governed by a fundamental Poisson bracket relation that fits into the r-s-matrix formalism for non-ultralocal integrable models first discussed by Maillet. The matrices r and s are computed explicitly and, being field dependent, satisfy fundamental Poisson bracket relations of their own, which can be expressed in terms of a new numerical matrix c. It is proposed that all these Poisson brackets taken together are representation conditions for a new kind of algebra which, for this class of models, replaces the classical Yang-Baxter algebra governing the canonical structure of ultralocal models. The Poisson brackets for the transition matrices are also computed, and the notorious regularization problem associated with the definition of the Poisson brackets for the monodromy matrices is discussed. (orig.)
DEFF Research Database (Denmark)
Fokianos, Konstantinos; Rahbek, Anders Christian; Tjøstheim, Dag
This paper considers geometric ergodicity and likelihood based inference for linear and nonlinear Poisson autoregressions. In the linear case the conditional mean is linked linearly to its past values as well as the observed values of the Poisson process. This also applies to the conditional...... variance, implying an interpretation as an integer valued GARCH process. In a nonlinear conditional Poisson model, the conditional mean is a nonlinear function of its past values and a nonlinear function of past observations. As a particular example an exponential autoregressive Poisson model for time...... series is considered. Under geometric ergodicity the maximum likelihood estimators of the parameters are shown to be asymptotically Gaussian in the linear model. In addition we provide a consistent estimator of the asymptotic covariance, which is used in the simulations and the analysis of some...
Application of the Hyper-Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes.
Khazraee, S Hadi; Sáez-Castillo, Antonio Jose; Geedipally, Srinivas Reddy; Lord, Dominique
2015-05-01
The hyper-Poisson distribution can handle both over- and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation-specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper-Poisson distribution in analyzing motor vehicle crash count data. The hyper-Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway-highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness-of-fit measures indicated that the hyper-Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper-Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway-Maxwell-Poisson model previously developed for the same data set. The advantages of the hyper-Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper-Poisson model can handle both over- and underdispersed crash data. Although not a major issue for the Conway-Maxwell-Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model. © 2014 Society for Risk Analysis.
Amalia, Junita; Purhadi, Otok, Bambang Widjanarko
2017-11-01
Poisson distribution is a discrete distribution with count data as the random variables and it has one parameter defines both mean and variance. Poisson regression assumes mean and variance should be same (equidispersion). Nonetheless, some case of the count data unsatisfied this assumption because variance exceeds mean (over-dispersion). The ignorance of over-dispersion causes underestimates in standard error. Furthermore, it causes incorrect decision in the statistical test. Previously, paired count data has a correlation and it has bivariate Poisson distribution. If there is over-dispersion, modeling paired count data is not sufficient with simple bivariate Poisson regression. Bivariate Poisson Inverse Gaussian Regression (BPIGR) model is mix Poisson regression for modeling paired count data within over-dispersion. BPIGR model produces a global model for all locations. In another hand, each location has different geographic conditions, social, cultural and economic so that Geographically Weighted Regression (GWR) is needed. The weighting function of each location in GWR generates a different local model. Geographically Weighted Bivariate Poisson Inverse Gaussian Regression (GWBPIGR) model is used to solve over-dispersion and to generate local models. Parameter estimation of GWBPIGR model obtained by Maximum Likelihood Estimation (MLE) method. Meanwhile, hypothesis testing of GWBPIGR model acquired by Maximum Likelihood Ratio Test (MLRT) method.
Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis.
Armstrong, Ben G; Gasparrini, Antonio; Tobias, Aurelio
2014-11-24
The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some limitations. In particular adjusting for overdispersion and auto-correlation in the counts is not possible. It has been established that a Poisson model for counts with stratum indicators gives identical estimates to those from conditional logistic regression and does not have these limitations, but it is little used, probably because of the overheads in estimating many stratum parameters. The conditional Poisson model avoids estimating stratum parameters by conditioning on the total event count in each stratum, thus simplifying the computing and increasing the number of strata for which fitting is feasible compared with the standard unconditional Poisson model. Unlike the conditional logistic model, the conditional Poisson model does not require expanding the data, and can adjust for overdispersion and auto-correlation. It is available in Stata, R, and other packages. By applying to some real data and using simulations, we demonstrate that conditional Poisson models were simpler to code and shorter to run than are conditional logistic analyses and can be fitted to larger data sets than possible with standard Poisson models. Allowing for overdispersion or autocorrelation was possible with the conditional Poisson model but when not required this model gave identical estimates to those from conditional logistic regression. Conditional Poisson regression models provide an alternative to case crossover analysis of stratified time series data with some advantages. The conditional Poisson model can also be used in other contexts in which primary control for confounding is by fine
[Application of detecting and taking overdispersion into account in Poisson regression model].
Bouche, G; Lepage, B; Migeot, V; Ingrand, P
2009-08-01
Researchers often use the Poisson regression model to analyze count data. Overdispersion can occur when a Poisson regression model is used, resulting in an underestimation of variance of the regression model parameters. Our objective was to take overdispersion into account and assess its impact with an illustration based on the data of a study investigating the relationship between use of the Internet to seek health information and number of primary care consultations. Three methods, overdispersed Poisson, a robust estimator, and negative binomial regression, were performed to take overdispersion into account in explaining variation in the number (Y) of primary care consultations. We tested overdispersion in the Poisson regression model using the ratio of the sum of Pearson residuals over the number of degrees of freedom (chi(2)/df). We then fitted the three models and compared parameter estimation to the estimations given by Poisson regression model. Variance of the number of primary care consultations (Var[Y]=21.03) was greater than the mean (E[Y]=5.93) and the chi(2)/df ratio was 3.26, which confirmed overdispersion. Standard errors of the parameters varied greatly between the Poisson regression model and the three other regression models. Interpretation of estimates from two variables (using the Internet to seek health information and single parent family) would have changed according to the model retained, with significant levels of 0.06 and 0.002 (Poisson), 0.29 and 0.09 (overdispersed Poisson), 0.29 and 0.13 (use of a robust estimator) and 0.45 and 0.13 (negative binomial) respectively. Different methods exist to solve the problem of underestimating variance in the Poisson regression model when overdispersion is present. The negative binomial regression model seems to be particularly accurate because of its theorical distribution ; in addition this regression is easy to perform with ordinary statistical software packages.
DEFF Research Database (Denmark)
Fokianos, Konstantinos; Rahbek, Anders Christian; Tjøstheim, Dag
2009-01-01
In this article we consider geometric ergodicity and likelihood-based inference for linear and nonlinear Poisson autoregression. In the linear case, the conditional mean is linked linearly to its past values, as well as to the observed values of the Poisson process. This also applies to the condi......In this article we consider geometric ergodicity and likelihood-based inference for linear and nonlinear Poisson autoregression. In the linear case, the conditional mean is linked linearly to its past values, as well as to the observed values of the Poisson process. This also applies...... to the conditional variance, making possible interpretation as an integer-valued generalized autoregressive conditional heteroscedasticity process. In a nonlinear conditional Poisson model, the conditional mean is a nonlinear function of its past values and past observations. As a particular example, we consider...... ergodicity proceeds via Markov theory and irreducibility. Finding transparent conditions for proving ergodicity turns out to be a delicate problem in the original model formulation. This problem is circumvented by allowing a perturbation of the model. We show that as the perturbations can be chosen...
Directory of Open Access Journals (Sweden)
Hossein Fallahzadeh
2017-05-01
Full Text Available Introduction: Different statistical methods can be used to analyze fertility data. When the response variable is discrete, Poisson model is applied. If the condition does not hold for the Poisson model, its generalized model will be applied. The goal of this study was to compare the efficiency of generalized Poisson regression model with the standard Poisson regression model in estimating the coefficient of effective factors onthe current number of children. Methods: This is a cross-sectional study carried out on a populationof married women within the age range of15-49 years in Kashan, Iran. The cluster sampling method was used for data collection. Clusters consisted ofthe urbanblocksdeterminedby the municipality.Atotal number of10clusters each containing30households was selected according to the health center's framework. The necessary data were then collected through a self-madequestionnaireanddirectinterviewswith women under study. Further, the data analysiswas performed by usingthe standard and generalizedPoisson regression models through theRsoftware. Results: The average number of children for each woman was 1.45 with a variance of 1.073.A significant relationship was observed between the husband's age, number of unwanted pregnancies, and the average durationof breastfeeding with the present number of children in the two standard and generalized Poisson regression models (p < 0.05.The mean ageof women participating in thisstudy was33.1± 7.57 years (from 25.53 years to 40.67, themean age of marriage was 20.09 ± 3.82 (from16.27 years to23.91, and themean age of their husbands was 37.9 ± 8.4years (from 29.5 years to 46.3. In the current study, the majority of women werein the age range of 30-35years old with the medianof 32years, however, most ofmen were in the age range of 35-40yearswith the median of37years. While 236of women did not have unwanted pregnancies, most participants of the present study had one unwanted pregnancy
DEFF Research Database (Denmark)
Fokianos, Konstantinos; Rahbæk, Anders; Tjøstheim, Dag
This paper considers geometric ergodicity and likelihood based inference for linear and nonlinear Poisson autoregressions. In the linear case the conditional mean is linked linearly to its past values as well as the observed values of the Poisson process. This also applies to the conditional...... proceeds via Markov theory and irreducibility. Finding transparent conditions for proving ergodicity turns out to be a delicate problem in the original model formulation. This problem is circumvented by allowing a perturbation of the model. We show that as the perturbations can be chosen to be arbitrarily...
Log-normal frailty models fitted as Poisson generalized linear mixed models.
Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver
2016-12-01
The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Statistical modelling of Poisson/log-normal data
International Nuclear Information System (INIS)
Miller, G.
2007-01-01
In statistical data fitting, self consistency is checked by examining the closeness of the quantity Χ 2 /NDF to 1, where Χ 2 is the sum of squares of data minus fit divided by standard deviation, and NDF is the number of data minus the number of fit parameters. In order to calculate Χ 2 one needs an expression for the standard deviation. In this note several alternative expressions for the standard deviation of data distributed according to a Poisson/log-normal distribution are proposed and evaluated by Monte Carlo simulation. Two preferred alternatives are identified. The use of replicate data to obtain uncertainty is problematic for a small number of replicates. A method to correct this problem is proposed. The log-normal approximation is good for sufficiently positive data. A modification of the log-normal approximation is proposed, which allows it to be used to test the hypothesis that the true value is zero. (authors)
Directory of Open Access Journals (Sweden)
Rodrigues-Motta Mariana
2008-07-01
Full Text Available Abstract Dark spots in the fleece area are often associated with dark fibres in wool, which limits its competitiveness with other textile fibres. Field data from a sheep experiment in Uruguay revealed an excess number of zeros for dark spots. We compared the performance of four Poisson and zero-inflated Poisson (ZIP models under four simulation scenarios. All models performed reasonably well under the same scenario for which the data were simulated. The deviance information criterion favoured a Poisson model with residual, while the ZIP model with a residual gave estimates closer to their true values under all simulation scenarios. Both Poisson and ZIP models with an error term at the regression level performed better than their counterparts without such an error. Field data from Corriedale sheep were analysed with Poisson and ZIP models with residuals. Parameter estimates were similar for both models. Although the posterior distribution of the sire variance was skewed due to a small number of rams in the dataset, the median of this variance suggested a scope for genetic selection. The main environmental factor was the age of the sheep at shearing. In summary, age related processes seem to drive the number of dark spots in this breed of sheep.
Simulation on Poisson and negative binomial models of count road accident modeling
Sapuan, M. S.; Razali, A. M.; Zamzuri, Z. H.; Ibrahim, K.
2016-11-01
Accident count data have often been shown to have overdispersion. On the other hand, the data might contain zero count (excess zeros). The simulation study was conducted to create a scenarios which an accident happen in T-junction with the assumption the dependent variables of generated data follows certain distribution namely Poisson and negative binomial distribution with different sample size of n=30 to n=500. The study objective was accomplished by fitting Poisson regression, negative binomial regression and Hurdle negative binomial model to the simulated data. The model validation was compared and the simulation result shows for each different sample size, not all model fit the data nicely even though the data generated from its own distribution especially when the sample size is larger. Furthermore, the larger sample size indicates that more zeros accident count in the dataset.
Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach.
Mohammadi, Tayeb; Kheiri, Soleiman; Sedehi, Morteza
2016-01-01
Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables "number of blood donation" and "number of blood deferral": as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models.
Bayesian spatial modeling of HIV mortality via zero-inflated Poisson models.
Musal, Muzaffer; Aktekin, Tevfik
2013-01-30
In this paper, we investigate the effects of poverty and inequality on the number of HIV-related deaths in 62 New York counties via Bayesian zero-inflated Poisson models that exhibit spatial dependence. We quantify inequality via the Theil index and poverty via the ratios of two Census 2000 variables, the number of people under the poverty line and the number of people for whom poverty status is determined, in each Zip Code Tabulation Area. The purpose of this study was to investigate the effects of inequality and poverty in addition to spatial dependence between neighboring regions on HIV mortality rate, which can lead to improved health resource allocation decisions. In modeling county-specific HIV counts, we propose Bayesian zero-inflated Poisson models whose rates are functions of both covariate and spatial/random effects. To show how the proposed models work, we used three different publicly available data sets: TIGER Shapefiles, Census 2000, and mortality index files. In addition, we introduce parameter estimation issues of Bayesian zero-inflated Poisson models and discuss MCMC method implications. Copyright © 2012 John Wiley & Sons, Ltd.
The Rasch Poisson Counts Model for Incomplete Data: An Application of the EM Algorithm.
Jansen, Margo G. H.
1995-01-01
The Rasch Poisson counts model is a latent trait model for the situation in which "K" tests are administered to "N" examinees and the test score is a count (repeated number of some event). A mixed model is presented that applies the EM algorithm and that can allow for missing data. (SLD)
Brownian motion and parabolic Anderson model in a renormalized Poisson potential
Chen, Xia; Kulik, Alexey M.
2012-01-01
A method known as renormalization is proposed for constructing some more physically realistic random potentials in a Poisson cloud. The Brownian motion in the renormalized random potential and related parabolic Anderson models are modeled. With the renormalization, for example, the models consistent to Newton’s law of universal attraction can be rigorously constructed.
A LATENT CLASS POISSON REGRESSION-MODEL FOR HETEROGENEOUS COUNT DATA
WEDEL, M; DESARBO, WS; BULT, [No Value; RAMASWAMY, [No Value
1993-01-01
In this paper an approach is developed that accommodates heterogeneity in Poisson regression models for count data. The model developed assumes that heterogeneity arises from a distribution of both the intercept and the coefficients of the explanatory variables. We assume that the mixing
Poisson regression for modeling count and frequency outcomes in trauma research.
Gagnon, David R; Doron-LaMarca, Susan; Bell, Margret; O'Farrell, Timothy J; Taft, Casey T
2008-10-01
The authors describe how the Poisson regression method for analyzing count or frequency outcome variables can be applied in trauma studies. The outcome of interest in trauma research may represent a count of the number of incidents of behavior occurring in a given time interval, such as acts of physical aggression or substance abuse. Traditional linear regression approaches assume a normally distributed outcome variable with equal variances over the range of predictor variables, and may not be optimal for modeling count outcomes. An application of Poisson regression is presented using data from a study of intimate partner aggression among male patients in an alcohol treatment program and their female partners. Results of Poisson regression and linear regression models are compared.
Sepúlveda, Nuno
2013-02-26
Background: The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model.Results: Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates.Conclusions: In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data. 2013 Seplveda et al.; licensee BioMed Central Ltd.
Misspecified poisson regression models for large-scale registry data
DEFF Research Database (Denmark)
Grøn, Randi; Gerds, Thomas A.; Andersen, Per K.
2016-01-01
working models that are then likely misspecified. To support and improve conclusions drawn from such models, we discuss methods for sensitivity analysis, for estimation of average exposure effects using aggregated data, and a semi-parametric bootstrap method to obtain robust standard errors. The methods...
Shiyko, Mariya P.; Li, Yuelin; Rindskopf, David
2012-01-01
Intensive longitudinal data (ILD) have become increasingly common in the social and behavioral sciences; count variables, such as the number of daily smoked cigarettes, are frequently used outcomes in many ILD studies. We demonstrate a generalized extension of growth mixture modeling (GMM) to Poisson-distributed ILD for identifying qualitatively…
The Fixed-Effects Zero-Inflated Poisson Model with an Application to Health Care Utilization
Majo, M.C.; van Soest, A.H.O.
2011-01-01
Response variables that are scored as counts and that present a large number of zeros often arise in quantitative health care analysis. We define a zero-in flated Poisson model with fixed-effects in both of its equations to identify respondent and health-related characteristics associated with
Modeling of Electrokinetic Processes Using the Nernst-Plank-Poisson System
DEFF Research Database (Denmark)
Paz-Garcia, Juan Manuel; Johannesson, Björn; Ottosen, Lisbeth M.
2010-01-01
Electrokinetic processes are known as the mobilization of species within the pore solution of porous materials under the effect of an external electric field. A finite elements model was implemented and used for the integration of the coupled Nernst-Plank-Poisson system of equations in order...
Multiple mortality modeling in Poisson Lee-Carter framework
D'Amato, V.; Haberman, S.; Piscopo, G.; Russolillo, M.; Trapani, L.
2016-01-01
The academic literature in longevity field has recently focused on models for detecting multiple population trends (D'Amato et al., 2012b; Njenga and Sherris, 2011; Russolillo et al., 2011, etc.). In particular, increasing interest has been shown about "related" population dynamics or "parent" populations characterized by similar socioeconomic conditions and eventually also by geographical proximity. These studies suggest dependence across multiple populations and common long-run relationship...
Business Cycle Models with Embodied Technological Change and Poisson Shocks
Schlegel, Christoph
2004-01-01
The first part analyzes an Endogenous Business Cycle model with embodied technological change. Households take an optimal decision about their spending for consumption and financing of R&D. The probability of a technology invention occurring is an increasing function of aggregate R&D expenditure in the whole economy. New technologies bring higher productivity, but rather than applying to the whole capital stock, they require a new vintage of capital, which first has to be accu...
The Poisson model limits in NBA basketball: Complexity in team sports
Martín-González, Juan Manuel; de Saá Guerra, Yves; García-Manso, Juan Manuel; Arriaza, Enrique; Valverde-Estévez, Teresa
2016-12-01
Team sports are frequently studied by researchers. There is presumption that scoring in basketball is a random process and that can be described using the Poisson Model. Basketball is a collaboration-opposition sport, where the non-linear local interactions among players are reflected in the evolution of the score that ultimately determines the winner. In the NBA, the outcomes of close games are often decided in the last minute, where fouls play a main role. We examined 6130 NBA games in order to analyze the time intervals between baskets and scoring dynamics. Most numbers of baskets (n) over a time interval (ΔT) follow a Poisson distribution, but some (e.g., ΔT = 10 s, n > 3) behave as a Power Law. The Poisson distribution includes most baskets in any game, in most game situations, but in close games in the last minute, the numbers of events are distributed following a Power Law. The number of events can be adjusted by a mixture of two distributions. In close games, both teams try to maintain their advantage solely in order to reach the last minute: a completely different game. For this reason, we propose to use the Poisson model as a reference. The complex dynamics will emerge from the limits of this model.
Hidden Markov models for zero-inflated Poisson counts with an application to substance use.
DeSantis, Stacia M; Bandyopadhyay, Dipankar
2011-06-30
Paradigms for substance abuse cue-reactivity research involve pharmacological or stressful stimulation designed to elicit stress and craving responses in cocaine-dependent subjects. It is unclear as to whether stress induced from participation in such studies increases drug-seeking behavior. We propose a 2-state Hidden Markov model to model the number of cocaine abuses per week before and after participation in a stress-and cue-reactivity study. The hypothesized latent state corresponds to 'high' or 'low' use. To account for a preponderance of zeros, we assume a zero-inflated Poisson model for the count data. Transition probabilities depend on the prior week's state, fixed demographic variables, and time-varying covariates. We adopt a Bayesian approach to model fitting, and use the conditional predictive ordinate statistic to demonstrate that the zero-inflated Poisson hidden Markov model outperforms other models for longitudinal count data. Copyright © 2011 John Wiley & Sons, Ltd.
Poisson regression approach for modeling fatal injury rates amongst Malaysian workers
International Nuclear Information System (INIS)
Kamarulzaman Ibrahim; Heng Khai Theng
2005-01-01
Many safety studies are based on the analysis carried out on injury surveillance data. The injury surveillance data gathered for the analysis include information on number of employees at risk of injury in each of several strata where the strata are defined in terms of a series of important predictor variables. Further insight into the relationship between fatal injury rates and predictor variables may be obtained by the poisson regression approach. Poisson regression is widely used in analyzing count data. In this study, poisson regression is used to model the relationship between fatal injury rates and predictor variables which are year (1995-2002), gender, recording system and industry type. Data for the analysis were obtained from PERKESO and Jabatan Perangkaan Malaysia. It is found that the assumption that the data follow poisson distribution has been violated. After correction for the problem of over dispersion, the predictor variables that are found to be significant in the model are gender, system of recording, industry type, two interaction effects (interaction between recording system and industry type and between year and industry type). Introduction Regression analysis is one of the most popular
Stochastic Interest Model Based on Compound Poisson Process and Applications in Actuarial Science
Directory of Open Access Journals (Sweden)
Shilong Li
2017-01-01
Full Text Available Considering stochastic behavior of interest rates in financial market, we construct a new class of interest models based on compound Poisson process. Different from the references, this paper describes the randomness of interest rates by modeling the force of interest with Poisson random jumps directly. To solve the problem in calculation of accumulated interest force function, one important integral technique is employed. And a conception called the critical value is introduced to investigate the validity condition of this new model. We also discuss actuarial present values of several life annuities under this new interest model. Simulations are done to illustrate the theoretical results and the effect of parameters in interest model on actuarial present values is also analyzed.
How does Poisson kriging compare to the popular BYM model for mapping disease risks?
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Gebreab Samson
2008-02-01
Full Text Available Abstract Background Geostatistical techniques are now available to account for spatially varying population sizes and spatial patterns in the mapping of disease rates. At first glance, Poisson kriging represents an attractive alternative to increasingly popular Bayesian spatial models in that: 1 it is easier to implement and less CPU intensive, and 2 it accounts for the size and shape of geographical units, avoiding the limitations of conditional auto-regressive (CAR models commonly used in Bayesian algorithms while allowing for the creation of isopleth risk maps. Both approaches, however, have never been compared in simulation studies, and there is a need to better understand their merits in terms of accuracy and precision of disease risk estimates. Results Besag, York and Mollie's (BYM model and Poisson kriging (point and area-to-area implementations were applied to age-adjusted lung and cervix cancer mortality rates recorded for white females in two contrasted county geographies: 1 state of Indiana that consists of 92 counties of fairly similar size and shape, and 2 four states in the Western US (Arizona, California, Nevada and Utah forming a set of 118 counties that are vastly different geographical units. The spatial support (i.e. point versus area has a much smaller impact on the results than the statistical methodology (i.e. geostatistical versus Bayesian models. Differences between methods are particularly pronounced in the Western US dataset: BYM model yields smoother risk surface and prediction variance that changes mainly as a function of the predicted risk, while the Poisson kriging variance increases in large sparsely populated counties. Simulation studies showed that the geostatistical approach yields smaller prediction errors, more precise and accurate probability intervals, and allows a better discrimination between counties with high and low mortality risks. The benefit of area-to-area Poisson kriging increases as the county
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Lope Virginia
2009-01-01
Full Text Available Abstract Background Non-Hodgkin's lymphomas (NHLs have been linked to proximity to industrial areas, but evidence regarding the health risk posed by residence near pollutant industries is very limited. The European Pollutant Emission Register (EPER is a public register that furnishes valuable information on industries that release pollutants to air and water, along with their geographical location. This study sought to explore the relationship between NHL mortality in small areas in Spain and environmental exposure to pollutant emissions from EPER-registered industries, using three Poisson-regression-based mathematical models. Methods Observed cases were drawn from mortality registries in Spain for the period 1994–2003. Industries were grouped into the following sectors: energy; metal; mineral; organic chemicals; waste; paper; food; and use of solvents. Populations having an industry within a radius of 1, 1.5, or 2 kilometres from the municipal centroid were deemed to be exposed. Municipalities outside those radii were considered as reference populations. The relative risks (RRs associated with proximity to pollutant industries were estimated using the following methods: Poisson Regression; mixed Poisson model with random provincial effect; and spatial autoregressive modelling (BYM model. Results Only proximity of paper industries to population centres (>2 km could be associated with a greater risk of NHL mortality (mixed model: RR:1.24, 95% CI:1.09–1.42; BYM model: RR:1.21, 95% CI:1.01–1.45; Poisson model: RR:1.16, 95% CI:1.06–1.27. Spatial models yielded higher estimates. Conclusion The reported association between exposure to air pollution from the paper, pulp and board industry and NHL mortality is independent of the model used. Inclusion of spatial random effects terms in the risk estimate improves the study of associations between environmental exposures and mortality. The EPER could be of great utility when studying the effects of
Numerical solution of continuous-time DSGE models under Poisson uncertainty
DEFF Research Database (Denmark)
Posch, Olaf; Trimborn, Timo
We propose a simple and powerful method for determining the transition process in continuous-time DSGE models under Poisson uncertainty numerically. The idea is to transform the system of stochastic differential equations into a system of functional differential equations of the retarded type. We...... then use the Waveform Relaxation algorithm to provide a guess of the policy function and solve the resulting system of ordinary differential equations by standard methods and fix-point iteration. Analytical solutions are provided as a benchmark from which our numerical method can be used to explore broader...... classes of models. We illustrate the algorithm simulating both the stochastic neoclassical growth model and the Lucas model under Poisson uncertainty which is motivated by the Barro-Rietz rare disaster hypothesis. We find that, even for non-linear policy functions, the maximum (absolute) error is very...
A Local Poisson Graphical Model for inferring networks from sequencing data.
Allen, Genevera I; Liu, Zhandong
2013-09-01
Gaussian graphical models, a class of undirected graphs or Markov Networks, are often used to infer gene networks based on microarray expression data. Many scientists, however, have begun using high-throughput sequencing technologies such as RNA-sequencing or next generation sequencing to measure gene expression. As the resulting data consists of counts of sequencing reads for each gene, Gaussian graphical models are not optimal for this discrete data. In this paper, we propose a novel method for inferring gene networks from sequencing data: the Local Poisson Graphical Model. Our model assumes a Local Markov property where each variable conditional on all other variables is Poisson distributed. We develop a neighborhood selection algorithm to fit our model locally by performing a series of l1 penalized Poisson, or log-linear, regressions. This yields a fast parallel algorithm for estimating networks from next generation sequencing data. In simulations, we illustrate the effectiveness of our methods for recovering network structure from count data. A case study on breast cancer microRNAs (miRNAs), a novel application of graphical models, finds known regulators of breast cancer genes and discovers novel miRNA clusters and hubs that are targets for future research.
A Poisson-Fault Model for Testing Power Transformers in Service
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Dengfu Zhao
2014-01-01
Full Text Available This paper presents a method for assessing the instant failure rate of a power transformer under different working conditions. The method can be applied to a dataset of a power transformer under periodic inspections and maintenance. We use a Poisson-fault model to describe failures of a power transformer. When investigating a Bayes estimate of the instant failure rate under the model, we find that complexities of a classical method and a Monte Carlo simulation are unacceptable. Through establishing a new filtered estimate of Poisson process observations, we propose a quick algorithm of the Bayes estimate of the instant failure rate. The proposed algorithm is tested by simulation datasets of a power transformer. For these datasets, the proposed estimators of parameters of the model have better performance than other estimators. The simulation results reveal the suggested algorithms are quickest among three candidates.
Mohebbi, Mohammadreza; Wolfe, Rory; Jolley, Damien
2011-10-03
Analytic methods commonly used in epidemiology do not account for spatial correlation between observations. In regression analyses, omission of that autocorrelation can bias parameter estimates and yield incorrect standard error estimates. We used age standardised incidence ratios (SIRs) of esophageal cancer (EC) from the Babol cancer registry from 2001 to 2005, and extracted socioeconomic indices from the Statistical Centre of Iran. The following models for SIR were used: (1) Poisson regression with agglomeration-specific nonspatial random effects; (2) Poisson regression with agglomeration-specific spatial random effects. Distance-based and neighbourhood-based autocorrelation structures were used for defining the spatial random effects and a pseudolikelihood approach was applied to estimate model parameters. The Bayesian information criterion (BIC), Akaike's information criterion (AIC) and adjusted pseudo R2, were used for model comparison. A Gaussian semivariogram with an effective range of 225 km best fit spatial autocorrelation in agglomeration-level EC incidence. The Moran's I index was greater than its expected value indicating systematic geographical clustering of EC. The distance-based and neighbourhood-based Poisson regression estimates were generally similar. When residual spatial dependence was modelled, point and interval estimates of covariate effects were different to those obtained from the nonspatial Poisson model. The spatial pattern evident in the EC SIR and the observation that point estimates and standard errors differed depending on the modelling approach indicate the importance of accounting for residual spatial correlation in analyses of EC incidence in the Caspian region of Iran. Our results also illustrate that spatial smoothing must be applied with care.
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Jolley Damien
2011-10-01
Full Text Available Abstract Background Analytic methods commonly used in epidemiology do not account for spatial correlation between observations. In regression analyses, omission of that autocorrelation can bias parameter estimates and yield incorrect standard error estimates. Methods We used age standardised incidence ratios (SIRs of esophageal cancer (EC from the Babol cancer registry from 2001 to 2005, and extracted socioeconomic indices from the Statistical Centre of Iran. The following models for SIR were used: (1 Poisson regression with agglomeration-specific nonspatial random effects; (2 Poisson regression with agglomeration-specific spatial random effects. Distance-based and neighbourhood-based autocorrelation structures were used for defining the spatial random effects and a pseudolikelihood approach was applied to estimate model parameters. The Bayesian information criterion (BIC, Akaike's information criterion (AIC and adjusted pseudo R2, were used for model comparison. Results A Gaussian semivariogram with an effective range of 225 km best fit spatial autocorrelation in agglomeration-level EC incidence. The Moran's I index was greater than its expected value indicating systematic geographical clustering of EC. The distance-based and neighbourhood-based Poisson regression estimates were generally similar. When residual spatial dependence was modelled, point and interval estimates of covariate effects were different to those obtained from the nonspatial Poisson model. Conclusions The spatial pattern evident in the EC SIR and the observation that point estimates and standard errors differed depending on the modelling approach indicate the importance of accounting for residual spatial correlation in analyses of EC incidence in the Caspian region of Iran. Our results also illustrate that spatial smoothing must be applied with care.
Pareto genealogies arising from a Poisson branching evolution model with selection.
Huillet, Thierry E
2014-02-01
We study a class of coalescents derived from a sampling procedure out of N i.i.d. Pareto(α) random variables, normalized by their sum, including β-size-biasing on total length effects (β Poisson-Dirichlet (α, -β) Ξ-coalescent (α ε[0, 1)), or to a family of continuous-time Beta (2 - α, α - β)Λ-coalescents (α ε[1, 2)), or to the Kingman coalescent (α ≥ 2). We indicate that this class of coalescent processes (and their scaling limits) may be viewed as the genealogical processes of some forward in time evolving branching population models including selection effects. In such constant-size population models, the reproduction step, which is based on a fitness-dependent Poisson Point Process with scaling power-law(α) intensity, is coupled to a selection step consisting of sorting out the N fittest individuals issued from the reproduction step.
Studies on a Double Poisson-Geometric Insurance Risk Model with Interference
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Yujuan Huang
2013-01-01
Full Text Available This paper mainly studies a generalized double Poisson-Geometric insurance risk model. By martingale and stopping time approach, we obtain adjustment coefficient equation, the Lundberg inequality, and the formula for the ruin probability. Also the Laplace transformation of the time when the surplus reaches a given level for the first time is discussed, and the expectation and its variance are obtained. Finally, we give the numerical examples.
Statistical Assessement on Cancer Risks of Ionizing Radiation and Smoking Based on Poisson Models
Tomita, Makoto; Otake, Masanori
2001-01-01
In many epidemiological and medical studies, a number of cancer motralities in catagorical classification may be considered as having Poisson distribution with person-years at risk depending upon time. The cancer mortalities have been evaluated by additive or multiplicative models with regard to background and excess risks based on several covariances such as sex, age at the time of bombings, time at exposure, or ionizing radiation, cigarette smoking habits, duration of smoking habits, etc. A...
Zero inflated Poisson and negative binomial regression models: application in education.
Salehi, Masoud; Roudbari, Masoud
2015-01-01
The number of failed courses and semesters in students are indicators of their performance. These amounts have zero inflated (ZI) distributions. Using ZI Poisson and negative binomial distributions we can model these count data to find the associated factors and estimate the parameters. This study aims at to investigate the important factors related to the educational performance of students. This cross-sectional study performed in 2008-2009 at Iran University of Medical Sciences (IUMS) with a population of almost 6000 students, 670 students selected using stratified random sampling. The educational and demographical data were collected using the University records. The study design was approved at IUMS and the students' data kept confidential. The descriptive statistics and ZI Poisson and negative binomial regressions were used to analyze the data. The data were analyzed using STATA. In the number of failed semesters, Poisson and negative binomial distributions with ZI, students' total average and quota system had the most roles. For the number of failed courses, total average, and being in undergraduate or master levels had the most effect in both models. In all models the total average have the most effect on the number of failed courses or semesters. The next important factor is quota system in failed semester and undergraduate and master levels in failed courses. Therefore, average has an important inverse effect on the numbers of failed courses and semester.
Modeling Repeated Count Data : Some Extensions of the Rasch Poisson Counts Model
van Duijn, M.A.J.; Jansen, Margo
1995-01-01
We consider data that can be summarized as an N X K table of counts-for example, test data obtained by administering K tests to N subjects. The cell entries y(ij) are assumed to be conditionally independent Poisson-distributed random variables, given the NK Poisson intensity parameters mu(ij). The
Poisson versus threshold models for genetic analysis of clinical mastitis in US Holsteins.
Vazquez, A I; Weigel, K A; Gianola, D; Bates, D M; Perez-Cabal, M A; Rosa, G J M; Chang, Y M
2009-10-01
Typically, clinical mastitis is coded as the presence or absence of disease in a given lactation, and records are analyzed with either linear models or binary threshold models. Because the presence of mastitis may include cows with multiple episodes, there is a loss of information when counts are treated as binary responses. Poisson models are appropriated for random variables measured as the number of events, and although these models are used extensively in studying the epidemiology of mastitis, they have rarely been used for studying the genetic aspects of mastitis. Ordinal threshold models are pertinent for ordered categorical responses; although one can hypothesize that the number of clinical mastitis episodes per animal reflects a continuous underlying increase in mastitis susceptibility, these models have rarely been used in genetic analysis of mastitis. The objective of this study was to compare probit, Poisson, and ordinal threshold models for the genetic evaluation of US Holstein sires for clinical mastitis. Mastitis was measured as a binary trait or as the number of mastitis cases. Data from 44,908 first-parity cows recorded in on-farm herd management software were gathered, edited, and processed for the present study. The cows were daughters of 1,861 sires, distributed over 94 herds. Predictive ability was assessed via a 5-fold cross-validation using 2 loss functions: mean squared error of prediction (MSEP) as the end point and a cost difference function. The heritability estimates were 0.061 for mastitis measured as a binary trait in the probit model and 0.085 and 0.132 for the number of mastitis cases in the ordinal threshold and Poisson models, respectively; because of scale differences, only the probit and ordinal threshold models are directly comparable. Among healthy animals, MSEP was smallest for the probit model, and the cost function was smallest for the ordinal threshold model. Among diseased animals, MSEP and the cost function were smallest
Bayesian Estimation Of Shift Point In Poisson Model Under Asymmetric Loss Functions
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uma srivastava
2012-01-01
Full Text Available The paper deals with estimating shift point which occurs in any sequence of independent observations of Poisson model in statistical process control. This shift point occurs in the sequence when i.e. m life data are observed. The Bayes estimator on shift point 'm' and before and after shift process means are derived for symmetric and asymmetric loss functions under informative and non informative priors. The sensitivity analysis of Bayes estimators are carried out by simulation and numerical comparisons with R-programming. The results shows the effectiveness of shift in sequence of Poisson disribution .
Receiver design for SPAD-based VLC systems under Poisson-Gaussian mixed noise model.
Mao, Tianqi; Wang, Zhaocheng; Wang, Qi
2017-01-23
Single-photon avalanche diode (SPAD) is a promising photosensor because of its high sensitivity to optical signals in weak illuminance environment. Recently, it has drawn much attention from researchers in visible light communications (VLC). However, existing literature only deals with the simplified channel model, which only considers the effects of Poisson noise introduced by SPAD, but neglects other noise sources. Specifically, when an analog SPAD detector is applied, there exists Gaussian thermal noise generated by the transimpedance amplifier (TIA) and the digital-to-analog converter (D/A). Therefore, in this paper, we propose an SPAD-based VLC system with pulse-amplitude-modulation (PAM) under Poisson-Gaussian mixed noise model, where Gaussian-distributed thermal noise at the receiver is also investigated. The closed-form conditional likelihood of received signals is derived using the Laplace transform and the saddle-point approximation method, and the corresponding quasi-maximum-likelihood (quasi-ML) detector is proposed. Furthermore, the Poisson-Gaussian-distributed signals are converted to Gaussian variables with the aid of the generalized Anscombe transform (GAT), leading to an equivalent additive white Gaussian noise (AWGN) channel, and a hard-decision-based detector is invoked. Simulation results demonstrate that, the proposed GAT-based detector can reduce the computational complexity with marginal performance loss compared with the proposed quasi-ML detector, and both detectors are capable of accurately demodulating the SPAD-based PAM signals.
The Stochastic stability of a Logistic model with Poisson white noise
International Nuclear Information System (INIS)
Duan Dong-Hai; Xu Wei; Zhou Bing-Chang; Su Jun
2011-01-01
The stochastic stability of a logistic model subjected to the effect of a random natural environment, modeled as Poisson white noise process, is investigated. The properties of the stochastic response are discussed for calculating the Lyapunov exponent, which had proven to be the most useful diagnostic tool for the stability of dynamical systems. The generalised Itô differentiation formula is used to analyse the stochastic stability of the response. The results indicate that the stability of the response is related to the intensity and amplitude distribution of the environment noise and the growth rate of the species. (general)
The Stochastic stability of a Logistic model with Poisson white noise
Duan, Dong-Hai; Xu, Wei; Su, Jun; Zhou, Bing-Chang
2011-03-01
The stochastic stability of a logistic model subjected to the effect of a random natural environment, modeled as Poisson white noise process, is investigated. The properties of the stochastic response are discussed for calculating the Lyapunov exponent, which had proven to be the most useful diagnostic tool for the stability of dynamical systems. The generalised Itô differentiation formula is used to analyse the stochastic stability of the response. The results indicate that the stability of the response is related to the intensity and amplitude distribution of the environment noise and the growth rate of the species. Project supported by the National Natural Science Foundation of China (Grant Nos. 10872165 and 10932009).
A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data
Gallopin, Mélina; Rau, Andrea; Jaffrézic, Florence
2013-01-01
Gene network inference from transcriptomic data is an important methodological challenge and a key aspect of systems biology. Although several methods have been proposed to infer networks from microarray data, there is a need for inference methods able to model RNA-seq data, which are count-based and highly variable. In this work we propose a hierarchical Poisson log-normal model with a Lasso penalty to infer gene networks from RNA-seq data; this model has the advantage of directly modelling discrete data and accounting for inter-sample variance larger than the sample mean. Using real microRNA-seq data from breast cancer tumors and simulations, we compare this method to a regularized Gaussian graphical model on log-transformed data, and a Poisson log-linear graphical model with a Lasso penalty on power-transformed data. For data simulated with large inter-sample dispersion, the proposed model performs better than the other methods in terms of sensitivity, specificity and area under the ROC curve. These results show the necessity of methods specifically designed for gene network inference from RNA-seq data. PMID:24147011
Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data.
Achcar, Jorge Alberto; Martinez, Edson Zangiacomi; Souza, Aparecida Doniseti Pires de; Tachibana, Vilma Mayumi; Flores, Edilson Ferreira
2011-01-01
Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using bayesian spatiotemporal methods. We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the bayesian paradigm is a good strategy for modeling malaria counts.
Coley, Rebecca Yates; Browna, Elizabeth R.
2016-01-01
Inconsistent results in recent HIV prevention trials of pre-exposure prophylactic interventions may be due to heterogeneity in risk among study participants. Intervention effectiveness is most commonly estimated with the Cox model, which compares event times between populations. When heterogeneity is present, this population-level measure underestimates intervention effectiveness for individuals who are at risk. We propose a likelihood-based Bayesian hierarchical model that estimates the individual-level effectiveness of candidate interventions by accounting for heterogeneity in risk with a compound Poisson-distributed frailty term. This model reflects the mechanisms of HIV risk and allows that some participants are not exposed to HIV and, therefore, have no risk of seroconversion during the study. We assess model performance via simulation and apply the model to data from an HIV prevention trial. PMID:26869051
Non-Poisson counting statistics of a hybrid G-M counter dead time model
International Nuclear Information System (INIS)
Lee, Sang Hoon; Jae, Moosung; Gardner, Robin P.
2007-01-01
The counting statistics of a G-M counter with a considerable dead time event rate deviates from Poisson statistics. Important characteristics such as observed counting rates as a function true counting rates, variances and interval distributions were analyzed for three dead time models, non-paralyzable, paralyzable and hybrid, with the help of GMSIM, a Monte Carlo dead time effect simulator. The simulation results showed good agreements with the models in observed counting rates and variances. It was found through GMSIM simulations that the interval distribution for the hybrid model showed three distinctive regions, a complete cutoff region for the duration of the total dead time, a degraded exponential and an enhanced exponential regions. By measuring the cutoff and the duration of degraded exponential from the pulse interval distribution, it is possible to evaluate the two dead times in the hybrid model
The modified drift-Poisson model: Analogies with geophysical flows and Rossby waves
International Nuclear Information System (INIS)
Castillo-Negrete, D. del; Finn, J. M.; Barnes, D. C.
1999-01-01
We discuss an analogy between magnetically confined nonneutral plasmas and geophysical fluid dynamics. The analogy has its roots in the modified drift Poisson model, a recently proposed model that takes into account the plasma compression due to the variations of the plasma length [1]. The conservation of the line integrated density in the new model is analogous to the conservation of potential vorticity in the shallow water equations, and the variation of the plasma length is isomorphic to variations in the Coriolis parameter with latitude or to topography variations in the quasigeostrophic dynamics. We discuss a new class of linear and nonlinear waves that owe their existence to the variations of the plasma length. These modes are the analog of Rossby waves in geophysical flows
The Allan variance in the presence of a compound Poisson process modelling clock frequency jumps
Formichella, Valerio
2016-12-01
Atomic clocks can be affected by frequency jumps occurring at random times and with a random amplitude. The frequency jumps degrade the clock stability and this is captured by the Allan variance. In this work we assume that the random jumps can be modelled by a compound Poisson process, independent of the other stochastic and deterministic processes affecting the clock stability. Then, we derive the analytical expression of the Allan variance of a jumping clock. We find that the analytical Allan variance does not depend on the actual shape of the jumps amplitude distribution, but only on its first and second moments, and its final form is the same as for a clock with a random walk of frequency and a frequency drift. We conclude that the Allan variance cannot distinguish between a compound Poisson process and a Wiener process, hence it may not be sufficient to correctly identify the fundamental noise processes affecting a clock. The result is general and applicable to any oscillator, whose frequency is affected by a jump process with the described statistics.
Borchers, D L; Langrock, R
2015-12-01
We develop maximum likelihood methods for line transect surveys in which animals go undetected at distance zero, either because they are stochastically unavailable while within view or because they are missed when they are available. These incorporate a Markov-modulated Poisson process model for animal availability, allowing more clustered availability events than is possible with Poisson availability models. They include a mark-recapture component arising from the independent-observer survey, leading to more accurate estimation of detection probability given availability. We develop models for situations in which (a) multiple detections of the same individual are possible and (b) some or all of the availability process parameters are estimated from the line transect survey itself, rather than from independent data. We investigate estimator performance by simulation, and compare the multiple-detection estimators with estimators that use only initial detections of individuals, and with a single-observer estimator. Simultaneous estimation of detection function parameters and availability model parameters is shown to be feasible from the line transect survey alone with multiple detections and double-observer data but not with single-observer data. Recording multiple detections of individuals improves estimator precision substantially when estimating the availability model parameters from survey data, and we recommend that these data be gathered. We apply the methods to estimate detection probability from a double-observer survey of North Atlantic minke whales, and find that double-observer data greatly improve estimator precision here too. © 2015 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.
Zero-Inflated Poisson Modeling of Fall Risk Factors in Community-Dwelling Older Adults.
Jung, Dukyoo; Kang, Younhee; Kim, Mi Young; Ma, Rye-Won; Bhandari, Pratibha
2016-02-01
The aim of this study was to identify risk factors for falls among community-dwelling older adults. The study used a cross-sectional descriptive design. Self-report questionnaires were used to collect data from 658 community-dwelling older adults and were analyzed using logistic and zero-inflated Poisson (ZIP) regression. Perceived health status was a significant factor in the count model, and fall efficacy emerged as a significant predictor in the logistic models. The findings suggest that fall efficacy is important for predicting not only faller and nonfaller status but also fall counts in older adults who may or may not have experienced a previous fall. The fall predictors identified in this study--perceived health status and fall efficacy--indicate the need for fall-prevention programs tailored to address both the physical and psychological issues unique to older adults. © The Author(s) 2014.
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Hyungsuk Tak
2017-06-01
Full Text Available Rgbp is an R package that provides estimates and verifiable confidence intervals for random effects in two-level conjugate hierarchical models for overdispersed Gaussian, Poisson, and binomial data. Rgbp models aggregate data from k independent groups summarized by observed sufficient statistics for each random effect, such as sample means, possibly with covariates. Rgbp uses approximate Bayesian machinery with unique improper priors for the hyper-parameters, which leads to good repeated sampling coverage properties for random effects. A special feature of Rgbp is an option that generates synthetic data sets to check whether the interval estimates for random effects actually meet the nominal confidence levels. Additionally, Rgbp provides inference statistics for the hyper-parameters, e.g., regression coefficients.
Narukawa, Masaki; Nohara, Katsuhito
2018-04-01
This study proposes an estimation approach to panel count data, truncated at zero, in order to apply a contingent behavior travel cost method to revealed and stated preference data collected via a web-based survey. We develop zero-truncated panel Poisson mixture models by focusing on respondents who visited a site. In addition, we introduce an inverse Gaussian distribution to unobserved individual heterogeneity as an alternative to a popular gamma distribution, making it possible to capture effectively the long tail typically observed in trip data. We apply the proposed method to estimate the impact on tourism benefits in Fukushima Prefecture as a result of the Fukushima Nuclear Power Plant No. 1 accident. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Vidalis, M.
2012-01-01
Full Text Available In this work a two echelon merge supply chain is examined. Specifically, two non identical reliable suppliers feed a distribution centre with a shared buffer. The first echelon consists of the distribution centre and the shared buffer, the second echelon includes two non identical reliable suppliers. There is an unlimited supply of materials to suppliers and an unlimited capacity shipping area after the distribution centre. In other words, suppliers are never starved, and the distribution centre is never blocked. The materials are processed by suppliers with rates following the Erlang distribution. The distribution centre has a reliable machine that pushes material with service times following the Erlang distribution. Blocking appears when one or more suppliers finish their process and try to feed the buffer that is full. The supply network is modelled as a continuous time Markov process with discrete states. The structures of the transition matrices of those systems are explored and a computational algorithm is developed. Our aim is to generate stationary distributions for different values of system's parameters so as the various measures of the system can be estimated. Finally, for the mathematical programming model and the rest of the calculations the Matlab software is used.
Identification of temporal patterns in the seismicity of Sumatra using Poisson Hidden Markov models
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Katerina Orfanogiannaki
2014-05-01
Full Text Available On 26 December 2004 and 28 March 2005 two large earthquakes occurred between the Indo-Australian and the southeastern Eurasian plates with moment magnitudes Mw=9.1 and Mw=8.6, respectively. Complete data (mb≥4.2 of the post-1993 time interval have been used to apply Poisson Hidden Markov models (PHMMs for identifying temporal patterns in the time series of the two earthquake sequences. Each time series consists of earthquake counts, in given and constant time units, in the regions determined by the aftershock zones of the two mainshocks. In PHMMs each count is generated by one of m different Poisson processes that are called states. The series of states is unobserved and is in fact a Markov chain. The model incorporates a varying seismicity rate, it assigns a different rate to each state and it detects the changes on the rate over time. In PHMMs unobserved factors, related to the local properties of the region are considered affecting the earthquake occurrence rate. Estimation and interpretation of the unobserved sequence of states that underlie the data contribute to better understanding of the geophysical processes that take place in the region. We applied PHMMs to the time series of the two mainshocks and we estimated the unobserved sequences of states that underlie the data. The results obtained showed that the region of the 26 December 2004 earthquake was in state of low seismicity during almost the entire observation period. On the contrary, in the region of the 28 March 2005 earthquake the seismic activity is attributed to triggered seismicity, due to stress transfer from the region of the 2004 mainshock.
Arab, Ali; Holan, Scott H.; Wikle, Christopher K.; Wildhaber, Mark L.
2012-01-01
Ecological studies involving counts of abundance, presence–absence or occupancy rates often produce data having a substantial proportion of zeros. Furthermore, these types of processes are typically multivariate and only adequately described by complex nonlinear relationships involving externally measured covariates. Ignoring these aspects of the data and implementing standard approaches can lead to models that fail to provide adequate scientific understanding of the underlying ecological processes, possibly resulting in a loss of inferential power. One method of dealing with data having excess zeros is to consider the class of univariate zero-inflated generalized linear models. However, this class of models fails to address the multivariate and nonlinear aspects associated with the data usually encountered in practice. Therefore, we propose a semiparametric bivariate zero-inflated Poisson model that takes into account both of these data attributes. The general modeling framework is hierarchical Bayes and is suitable for a broad range of applications. We demonstrate the effectiveness of our model through a motivating example on modeling catch per unit area for multiple species using data from the Missouri River Benthic Fishes Study, implemented by the United States Geological Survey.
Poisson-Boltzmann theory of charged colloids: limits of the cell model for salty suspensions
International Nuclear Information System (INIS)
Denton, A R
2010-01-01
Thermodynamic properties of charge-stabilized colloidal suspensions and polyelectrolyte solutions are commonly modelled by implementing the mean-field Poisson-Boltzmann (PB) theory within a cell model. This approach models a bulk system by a single macroion, together with counterions and salt ions, confined to a symmetrically shaped, electroneutral cell. While easing numerical solution of the nonlinear PB equation, the cell model neglects microion-induced interactions and correlations between macroions, precluding modelling of macroion ordering phenomena. An alternative approach, which avoids the artificial constraints of cell geometry, exploits the mapping of a macroion-microion mixture onto a one-component model of pseudo-macroions governed by effective interparticle interactions. In practice, effective-interaction models are usually based on linear-screening approximations, which can accurately describe strong nonlinear screening only by incorporating an effective (renormalized) macroion charge. Combining charge renormalization and linearized PB theories, in both the cell model and an effective-interaction (cell-free) model, we compute osmotic pressures of highly charged colloids and monovalent microions, in Donnan equilibrium with a salt reservoir, over a range of concentrations. By comparing predictions with primitive model simulation data for salt-free suspensions, and with predictions from nonlinear PB theory for salty suspensions, we chart the limits of both the cell model and linear-screening approximations in modelling bulk thermodynamic properties. Up to moderately strong electrostatic couplings, the cell model proves accurate for predicting osmotic pressures of deionized (counterion-dominated) suspensions. With increasing salt concentration, however, the relative contribution of macroion interactions to the osmotic pressure grows, leading predictions from the cell and effective-interaction models to deviate. No evidence is found for a liquid
Ribeiro, Manuel Castro; Sousa, António Jorge; Pereira, Maria João
2016-05-01
The geographical distribution of health outcomes is influenced by socio-economic and environmental factors operating on different spatial scales. Geographical variations in relationships can be revealed with semi-parametric Geographically Weighted Poisson Regression (sGWPR), a model that can combine both geographically varying and geographically constant parameters. To decide whether a parameter should vary geographically, two models are compared: one in which all parameters are allowed to vary geographically and one in which all except the parameter being evaluated are allowed to vary geographically. The model with the lower corrected Akaike Information Criterion (AICc) is selected. Delivering model selection exclusively according to the AICc might hide important details in spatial variations of associations. We propose assisting the decision by using a Linear Model of Coregionalization (LMC). Here we show how LMC can refine sGWPR on ecological associations between socio-economic and environmental variables and low birth weight outcomes in the west-north-central region of Portugal. Copyright © 2016 Elsevier Ltd. All rights reserved.
SnIPRE: selection inference using a Poisson random effects model.
Directory of Open Access Journals (Sweden)
Kirsten E Eilertson
Full Text Available We present an approach for identifying genes under natural selection using polymorphism and divergence data from synonymous and non-synonymous sites within genes. A generalized linear mixed model is used to model the genome-wide variability among categories of mutations and estimate its functional consequence. We demonstrate how the model's estimated fixed and random effects can be used to identify genes under selection. The parameter estimates from our generalized linear model can be transformed to yield population genetic parameter estimates for quantities including the average selection coefficient for new mutations at a locus, the synonymous and non-synynomous mutation rates, and species divergence times. Furthermore, our approach incorporates stochastic variation due to the evolutionary process and can be fit using standard statistical software. The model is fit in both the empirical Bayes and Bayesian settings using the lme4 package in R, and Markov chain Monte Carlo methods in WinBUGS. Using simulated data we compare our method to existing approaches for detecting genes under selection: the McDonald-Kreitman test, and two versions of the Poisson random field based method MKprf. Overall, we find our method universally outperforms existing methods for detecting genes subject to selection using polymorphism and divergence data.
International Nuclear Information System (INIS)
Lewis, J.C.
2011-01-01
In a recent paper (Lewis, 2008) a class of models suitable for application to collision-sequence interference was introduced. In these models velocities are assumed to be completely randomized in each collision. The distribution of velocities was assumed to be Gaussian. The integrated induced dipole moment μk, for vector interference, or the scalar modulation μk, for scalar interference, was assumed to be a function of the impulse (integrated force) fk, or its magnitude fk, experienced by the molecule in a collision. For most of (Lewis, 2008) it was assumed that μk fk and μk fk, but it proved to be possible to extend the models, so that the magnitude of the induced dipole moment is equal to an arbitrary power or sum of powers of the intermolecular force. This allows estimates of the in filling of the interference dip by the dis proportionality of the induced dipole moment and force. One particular such model, using data from (Herman and Lewis, 2006), leads to the most realistic estimate for the in filling of the vector interference dip yet obtained. In (Lewis, 2008) the drastic assumption was made that collision times occurred at equal intervals. In the present paper that assumption is removed: the collision times are taken to form a Poisson process. This is much more realistic than the equal-intervals assumption. The interference dip is found to be a Lorentzian in this model
On the Fractional Poisson Process and the Discretized Stable Subordinator
Directory of Open Access Journals (Sweden)
Rudolf Gorenflo
2015-08-01
Full Text Available We consider the renewal counting number process N = N(t as a forward march over the non-negative integers with independent identically distributed waiting times. We embed the values of the counting numbers N in a “pseudo-spatial” non-negative half-line x ≥ 0 and observe that for physical time likewise we have t ≥ 0. Thus we apply the Laplace transform with respect to both variables x and t. Applying then a modification of the Montroll-Weiss-Cox formalism of continuous time random walk we obtain the essential characteristics of a renewal process in the transform domain and, if we are lucky, also in the physical domain. The process t = t(N of accumulation of waiting times is inverse to the counting number process, in honour of the Danish mathematician and telecommunication engineer A.K. Erlang we call it the Erlang process. It yields the probability of exactly n renewal events in the interval (0; t]. We apply our Laplace-Laplace formalism to the fractional Poisson process whose waiting times are of Mittag-Leffler type and to a renewal process whose waiting times are of Wright type. The process of Mittag-Leffler type includes as a limiting case the classical Poisson process, the process of Wright type represents the discretized stable subordinator and a re-scaled version of it was used in our method of parametric subordination of time-space fractional diffusion processes. Properly rescaling the counting number process N(t and the Erlang process t(N yields as diffusion limits the inverse stable and the stable subordinator, respectively.
Multivariate poisson lognormal modeling of crashes by type and severity on rural two lane highways.
Wang, Kai; Ivan, John N; Ravishanker, Nalini; Jackson, Eric
2017-02-01
In an effort to improve traffic safety, there has been considerable interest in estimating crash prediction models and identifying factors contributing to crashes. To account for crash frequency variations among crash types and severities, crash prediction models have been estimated by type and severity. The univariate crash count models have been used by researchers to estimate crashes by crash type or severity, in which the crash counts by type or severity are assumed to be independent of one another and modelled separately. When considering crash types and severities simultaneously, this may neglect the potential correlations between crash counts due to the presence of shared unobserved factors across crash types or severities for a specific roadway intersection or segment, and might lead to biased parameter estimation and reduce model accuracy. The focus on this study is to estimate crashes by both crash type and crash severity using the Integrated Nested Laplace Approximation (INLA) Multivariate Poisson Lognormal (MVPLN) model, and identify the different effects of contributing factors on different crash type and severity counts on rural two-lane highways. The INLA MVPLN model can simultaneously model crash counts by crash type and crash severity by accounting for the potential correlations among them and significantly decreases the computational time compared with a fully Bayesian fitting of the MVPLN model using Markov Chain Monte Carlo (MCMC) method. This paper describes estimation of MVPLN models for three-way stop controlled (3ST) intersections, four-way stop controlled (4ST) intersections, four-way signalized (4SG) intersections, and roadway segments on rural two-lane highways. Annual Average Daily traffic (AADT) and variables describing roadway conditions (including presence of lighting, presence of left-turn/right-turn lane, lane width and shoulder width) were used as predictors. A Univariate Poisson Lognormal (UPLN) was estimated by crash type and
Xie, Dexuan; Volkmer, Hans W.; Ying, Jinyong
2016-04-01
The nonlocal dielectric approach has led to new models and solvers for predicting electrostatics of proteins (or other biomolecules), but how to validate and compare them remains a challenge. To promote such a study, in this paper, two typical nonlocal dielectric models are revisited. Their analytical solutions are then found in the expressions of simple series for a dielectric sphere containing any number of point charges. As a special case, the analytical solution of the corresponding Poisson dielectric model is also derived in simple series, which significantly improves the well known Kirkwood's double series expansion. Furthermore, a convolution of one nonlocal dielectric solution with a commonly used nonlocal kernel function is obtained, along with the reaction parts of these local and nonlocal solutions. To turn these new series solutions into a valuable research tool, they are programed as a free fortran software package, which can input point charge data directly from a protein data bank file. Consequently, different validation tests can be quickly done on different proteins. Finally, a test example for a protein with 488 atomic charges is reported to demonstrate the differences between the local and nonlocal models as well as the importance of using the reaction parts to develop local and nonlocal dielectric solvers.
Winahju, W. S.; Mukarromah, A.; Putri, S.
2015-03-01
Leprosy is a chronic infectious disease caused by bacteria of leprosy (Mycobacterium leprae). Leprosy has become an important thing in Indonesia because its morbidity is quite high. Based on WHO data in 2014, in 2012 Indonesia has the highest number of new leprosy patients after India and Brazil with a contribution of 18.994 people (8.7% of the world). This number makes Indonesia automatically placed as the country with the highest number of leprosy morbidity of ASEAN countries. The province that most contributes to the number of leprosy patients in Indonesia is East Java. There are two kind of leprosy. They consist of pausibacillary and multibacillary. The morbidity of multibacillary leprosy is higher than pausibacillary leprosy. This paper will discuss modeling both of the number of multibacillary and pausibacillary leprosy patients as responses variables. These responses are count variables, so modeling will be conducted by using bivariate poisson regression method. Unit experiment used is in East Java, and predictors involved are: environment, demography, and poverty. The model uses data in 2012, and the result indicates that all predictors influence significantly.
Samat, N. A.; Ma'arof, S. H. Mohd Imam
2015-05-01
Disease mapping is a method to display the geographical distribution of disease occurrence, which generally involves the usage and interpretation of a map to show the incidence of certain diseases. Relative risk (RR) estimation is one of the most important issues in disease mapping. This paper begins by providing a brief overview of Chikungunya disease. This is followed by a review of the classical model used in disease mapping, based on the standardized morbidity ratio (SMR), which we then apply to our Chikungunya data. We then fit an extension of the classical model, which we refer to as a Poisson-Gamma model, when prior distributions for the relative risks are assumed known. Both results are displayed and compared using maps and we reveal a smoother map with fewer extremes values of estimated relative risk. The extensions of this paper will consider other methods that are relevant to overcome the drawbacks of the existing methods, in order to inform and direct government strategy for monitoring and controlling Chikungunya disease.
Ship-Track Models Based on Poisson-Distributed Port-Departure Times
National Research Council Canada - National Science Library
Heitmeyer, Richard
2006-01-01
... of those ships, and their nominal speeds. The probability law assumes that the ship departure times are Poisson-distributed with a time-varying departure rate and that the ship speeds and ship routes are statistically independent...
ADAPTIVE FINITE ELEMENT MODELING TECHNIQUES FOR THE POISSON-BOLTZMANN EQUATION
HOLST, MICHAEL; MCCAMMON, JAMES ANDREW; YU, ZEYUN; ZHOU, YOUNGCHENG; ZHU, YUNRONG
2011-01-01
We consider the design of an effective and reliable adaptive finite element method (AFEM) for the nonlinear Poisson-Boltzmann equation (PBE). We first examine the two-term regularization technique for the continuous problem recently proposed by Chen, Holst, and Xu based on the removal of the singular electrostatic potential inside biomolecules; this technique made possible the development of the first complete solution and approximation theory for the Poisson-Boltzmann equation, the first provably convergent discretization, and also allowed for the development of a provably convergent AFEM. However, in practical implementation, this two-term regularization exhibits numerical instability. Therefore, we examine a variation of this regularization technique which can be shown to be less susceptible to such instability. We establish a priori estimates and other basic results for the continuous regularized problem, as well as for Galerkin finite element approximations. We show that the new approach produces regularized continuous and discrete problems with the same mathematical advantages of the original regularization. We then design an AFEM scheme for the new regularized problem, and show that the resulting AFEM scheme is accurate and reliable, by proving a contraction result for the error. This result, which is one of the first results of this type for nonlinear elliptic problems, is based on using continuous and discrete a priori L∞ estimates to establish quasi-orthogonality. To provide a high-quality geometric model as input to the AFEM algorithm, we also describe a class of feature-preserving adaptive mesh generation algorithms designed specifically for constructing meshes of biomolecular structures, based on the intrinsic local structure tensor of the molecular surface. All of the algorithms described in the article are implemented in the Finite Element Toolkit (FETK), developed and maintained at UCSD. The stability advantages of the new regularization scheme
Multilevel poisson regression modelling for determining factors of dengue fever cases in bandung
Arundina, Davila Rubianti; Tantular, Bertho; Pontoh, Resa Septiani
2017-03-01
Scralatina or Dengue Fever is a kind of fever caused by serotype virus which Flavivirus genus and be known as Dengue Virus. Dengue Fever caused by Aedes Aegipty Mosquito bites who infected by a dengue virus. The study was conducted in 151 villages in Bandung. Health Analysts believes that there are two factors that affect the dengue cases, Internal factor (individual) and external factor (environment). The data who used in this research is hierarchical data. The method is used for hierarchical data modelling is multilevel method. Which is, the level 1 is village and level 2 is sub-district. According exploration data analysis, the suitable Multilevel Method is Random Intercept Model. Penalized Quasi Likelihood (PQL) approach on multilevel Poisson is a proper analysis to determine factors that affecting dengue cases in the city of Bandung. Clean and Healthy Behavior factor from the village level have an effect on the number of cases of dengue fever in the city of Bandung. Factor from the sub-district level has no effect.
A Tutorial of the Poisson Random Field Model in Population Genetics
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Praveen Sethupathy
2008-01-01
Full Text Available Population genetics is the study of allele frequency changes driven by various evolutionary forces such as mutation, natural selection, and random genetic drift. Although natural selection is widely recognized as a bona-fide phenomenon, the extent to which it drives evolution continues to remain unclear and controversial. Various qualitative techniques, or so-called “tests of neutrality”, have been introduced to detect signatures of natural selection. A decade and a half ago, Stanley Sawyer and Daniel Hartl provided a mathematical framework, referred to as the Poisson random field (PRF, with which to determine quantitatively the intensity of selection on a particular gene or genomic region. The recent availability of large-scale genetic polymorphism data has sparked widespread interest in genome-wide investigations of natural selection. To that end, the original PRF model is of particular interest for geneticists and evolutionary genomicists. In this article, we will provide a tutorial of the mathematical derivation of the original Sawyer and Hartl PRF model.
Vazquez, A I; Gianola, D; Bates, D; Weigel, K A; Heringstad, B
2009-02-01
Clinical mastitis is typically coded as presence/absence during some period of exposure, and records are analyzed with linear or binary data models. Because presence includes cows with multiple episodes, there is loss of information when a count is treated as a binary response. The Poisson model is designed for counting random variables, and although it is used extensively in epidemiology of mastitis, it has rarely been used for studying the genetics of mastitis. Many models have been proposed for genetic analysis of mastitis, but they have not been formally compared. The main goal of this study was to compare linear (Gaussian), Bernoulli (with logit link), and Poisson models for the purpose of genetic evaluation of sires for mastitis in dairy cattle. The response variables were clinical mastitis (CM; 0, 1) and number of CM cases (NCM; 0, 1, 2, ..). Data consisted of records on 36,178 first-lactation daughters of 245 Norwegian Red sires distributed over 5,286 herds. Predictive ability of models was assessed via a 3-fold cross-validation using mean squared error of prediction (MSEP) as the end-point. Between-sire variance estimates for NCM were 0.065 in Poisson and 0.007 in the linear model. For CM the between-sire variance was 0.093 in logit and 0.003 in the linear model. The ratio between herd and sire variances for the models with NCM response was 4.6 and 3.5 for Poisson and linear, respectively, and for model for CM was 3.7 in both logit and linear models. The MSEP for all cows was similar. However, within healthy animals, MSEP was 0.085 (Poisson), 0.090 (linear for NCM), 0.053 (logit), and 0.056 (linear for CM). For mastitic animals the MSEP values were 1.206 (Poisson), 1.185 (linear for NCM response), 1.333 (logit), and 1.319 (linear for CM response). The models for count variables had a better performance when predicting diseased animals and also had a similar performance between them. Logit and linear models for CM had better predictive ability for healthy
El-Basyouny, Karim; Barua, Sudip; Islam, Md Tazul
2014-12-01
Previous research shows that various weather elements have significant effects on crash occurrence and risk; however, little is known about how these elements affect different crash types. Consequently, this study investigates the impact of weather elements and sudden extreme snow or rain weather changes on crash type. Multivariate models were used for seven crash types using five years of daily weather and crash data collected for the entire City of Edmonton. In addition, the yearly trend and random variation of parameters across the years were analyzed by using four different modeling formulations. The proposed models were estimated in a full Bayesian context via Markov Chain Monte Carlo simulation. The multivariate Poisson lognormal model with yearly varying coefficients provided the best fit for the data according to Deviance Information Criteria. Overall, results showed that temperature and snowfall were statistically significant with intuitive signs (crashes decrease with increasing temperature; crashes increase as snowfall intensity increases) for all crash types, while rainfall was mostly insignificant. Previous snow showed mixed results, being statistically significant and positively related to certain crash types, while negatively related or insignificant in other cases. Maximum wind gust speed was found mostly insignificant with a few exceptions that were positively related to crash type. Major snow or rain events following a dry weather condition were highly significant and positively related to three crash types: Follow-Too-Close, Stop-Sign-Violation, and Ran-Off-Road crashes. The day-of-the-week dummy variables were statistically significant, indicating a possible weekly variation in exposure. Transportation authorities might use the above results to improve road safety by providing drivers with information regarding the risk of certain crash types for a particular weather condition. Copyright © 2014 Elsevier Ltd. All rights reserved.
Kysely, Jan; Picek, Jan; Beranova, Romana; Plavcova, Eva
2014-05-01
The study compares statistical models for estimating high quantiles of daily temperatures based on the homogeneous and non-homogeneous Poisson process, and their applications in climate model simulations. Both types of the models make use of non-stationary peaks-over-threshold method and the Generalized Pareto distribution (GPD) for modelling extremes, but they differ in how the dependence of the model parameters on time index is captured. The homogeneous Poisson process model assumes that the intensity of the process is constant and the threshold used to delimit extremes changes with time; the non-homogeneous Poisson process assumes that the intensity of the process depends on time while the threshold is kept constant (Coles 2001). The model for time-dependency of the GPD parameters is selected according to the likelihood ratio test. Statistical arguments are provided to support the homogeneous Poisson process model, in which temporal dependence of the threshold is modelled in terms of regression quantiles (Kysely et al. 2010). Dependence of the results on the quantile chosen for the threshold (95-99%) is evaluated. The extreme value models are applied to analyse scenarios of changes in high quantiles of daily temperatures (20-yr and 100-yr return values) in transient simulations of several GCMs and RCMs for the 21st century. References: Coles S. (2001) An Introduction to Statistical Modeling of Extreme Values. Springer, 208 pp. Kysely J., Picek J., Beranova R. (2010) Estimating extremes in climate change simulations using the peaks-over-threshold method with a non-stationary threshold. Global and Planetary Change, 72, 55-68.
Sharma, P; Mišković, Z L
2015-10-07
We present a model describing the electrostatic interactions across a structure that consists of a single layer of graphene with large area, lying above an oxide substrate of finite thickness, with its surface exposed to a thick layer of liquid electrolyte containing salt ions. Our goal is to analyze the co-operative screening of the potential fluctuation in a doped graphene due to randomness in the positions of fixed charged impurities in the oxide by the charge carriers in graphene and by the mobile ions in the diffuse layer of the electrolyte. In order to account for a possibly large potential drop in the diffuse later that may arise in an electrolytically gated graphene, we use a partially linearized Poisson-Boltzmann (PB) model of the electrolyte, in which we solve a fully nonlinear PB equation for the surface average of the potential in one dimension, whereas the lateral fluctuations of the potential in graphene are tackled by linearizing the PB equation about the average potential. In this way, we are able to describe the regime of equilibrium doping of graphene to large densities for arbitrary values of the ion concentration without restrictions to the potential drop in the electrolyte. We evaluate the electrostatic Green's function for the partially linearized PB model, which is used to express the screening contributions of the graphene layer and the nearby electrolyte by means of an effective dielectric function. We find that, while the screened potential of a single charged impurity at large in-graphene distances exhibits a strong dependence on the ion concentration in the electrolyte and on the doping density in graphene, in the case of a spatially correlated two-dimensional ensemble of impurities, this dependence is largely suppressed in the autocovariance of the fluctuating potential.
Numerical methods for a Poisson-Nernst-Planck-Fermi model of biological ion channels.
Liu, Jinn-Liang; Eisenberg, Bob
2015-07-01
Numerical methods are proposed for an advanced Poisson-Nernst-Planck-Fermi (PNPF) model for studying ion transport through biological ion channels. PNPF contains many more correlations than most models and simulations of channels, because it includes water and calculates dielectric properties consistently as outputs. This model accounts for the steric effect of ions and water molecules with different sizes and interstitial voids, the correlation effect of crowded ions with different valences, and the screening effect of polarized water molecules in an inhomogeneous aqueous electrolyte. The steric energy is shown to be comparable to the electrical energy under physiological conditions, demonstrating the crucial role of the excluded volume of particles and the voids in the natural function of channel proteins. Water is shown to play a critical role in both correlation and steric effects in the model. We extend the classical Scharfetter-Gummel (SG) method for semiconductor devices to include the steric potential for ion channels, which is a fundamental physical property not present in semiconductors. Together with a simplified matched interface and boundary (SMIB) method for treating molecular surfaces and singular charges of channel proteins, the extended SG method is shown to exhibit important features in flow simulations such as optimal convergence, efficient nonlinear iterations, and physical conservation. The generalized SG stability condition shows why the standard discretization (without SG exponential fitting) of NP equations may fail and that divalent Ca(2+) may cause more unstable discrete Ca(2+) fluxes than that of monovalent Na(+). Two different methods-called the SMIB and multiscale methods-are proposed for two different types of channels, namely, the gramicidin A channel and an L-type calcium channel, depending on whether water is allowed to pass through the channel. Numerical methods are first validated with constructed models whose exact solutions are
Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P
2014-06-26
To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.
Che Awang, Aznida; Azah Samat, Nor
2017-09-01
Leptospirosis is a disease caused by the infection of pathogenic species from the genus of Leptospira. Human can be infected by the leptospirosis from direct or indirect exposure to the urine of infected animals. The excretion of urine from the animal host that carries pathogenic Leptospira causes the soil or water to be contaminated. Therefore, people can become infected when they are exposed to contaminated soil and water by cut on the skin as well as open wound. It also can enter the human body by mucous membrane such nose, eyes and mouth, for example by splashing contaminated water or urine into the eyes or swallowing contaminated water or food. Currently, there is no vaccine available for the prevention or treatment of leptospirosis disease but this disease can be treated if it is diagnosed early to avoid any complication. The disease risk mapping is important in a way to control and prevention of disease. Using a good choice of statistical model will produce a good disease risk map. Therefore, the aim of this study is to estimate the relative risk for leptospirosis disease based initially on the most common statistic used in disease mapping called Standardized Morbidity Ratio (SMR) and Poisson-gamma model. This paper begins by providing a review of the SMR method and Poisson-gamma model, which we then applied to leptospirosis data of Kelantan, Malaysia. Both results are displayed and compared using graph, tables and maps. The result shows that the second method Poisson-gamma model produces better relative risk estimates compared to the SMR method. This is because the Poisson-gamma model can overcome the drawback of SMR where the relative risk will become zero when there is no observed leptospirosis case in certain regions. However, the Poisson-gamma model also faced problems where the covariate adjustment for this model is difficult and no possibility for allowing spatial correlation between risks in neighbouring areas. The problems of this model have
Yan, David
This thesis presents the one-dimensional equations, numerical method and simulations of a model to characterize the dynamical operation of an electrochemical cell. This model extends the current state-of-the art in that it accounts, in a primitive way, for the physics of the electrolyte/electrode interface and incorporates diffuse-charge dynamics, temperature coupling, surface coverage, and polarization phenomena. The one-dimensional equations account for a system with one or two mobile ions of opposite charge, and the electrode reaction we consider (when one is needed) is a one-electron electrodeposition reaction. Though the modeled system is far from representing a realistic electrochemical device, our results show a range of dynamics and behaviors which have not been observed previously, and explore the numerical challenges required when adding more complexity to a model. Furthermore, the basic transport equations (which are developed in three spatial dimensions) can in future accomodate the inclusion of additional physics, and coupling to more complex boundary conditions that incorporate two-dimensional surface phenomena and multi-rate reactions. In the model, the Poisson-Nernst-Planck equations are used to model diffusion and electromigration in an electrolyte, and the generalized Frumkin-Butler-Volmer equation is used to model reaction kinetics at electrodes. An energy balance equation is derived and coupled to the diffusion-migration equation. The model also includes dielectric polarization effects by introducing different values of the dielectric permittivity in different regions of the bulk, as well as accounting for surface coverage effects due to adsorption, and finite size "crowding", or steric effects. Advection effects are not modeled but could in future be incorporated. In order to solve the coupled PDE's, we use a variable step size second order scheme in time and finite differencing in space. Numerical tests are performed on a simplified system and
Liu, Jinn-Liang; Eisenberg, Bob
2018-02-01
The combinatorial explosion of empirical parameters in tens of thousands presents a tremendous challenge for extended Debye-Hückel models to calculate activity coefficients of aqueous mixtures of the most important salts in chemistry. The explosion of parameters originates from the phenomenological extension of the Debye-Hückel theory that does not take steric and correlation effects of ions and water into account. By contrast, the Poisson-Fermi theory developed in recent years treats ions and water molecules as nonuniform hard spheres of any size with interstitial voids and includes ion-water and ion-ion correlations. We present a Poisson-Fermi model and numerical methods for calculating the individual or mean activity coefficient of electrolyte solutions with any arbitrary number of ionic species in a large range of salt concentrations and temperatures. For each activity-concentration curve, we show that the Poisson-Fermi model requires only three unchanging parameters at most to well fit the corresponding experimental data. The three parameters are associated with the Born radius of the solvation energy of an ion in electrolyte solution that changes with salt concentrations in a highly nonlinear manner.
Czech Academy of Sciences Publication Activity Database
Jordanova, P.; Dušek, Jiří; Stehlík, M.
2013-01-01
Roč. 128, OCT 15 (2013), s. 124-134 ISSN 0169-7439 R&D Projects: GA ČR(CZ) GAP504/11/1151; GA MŠk(CZ) ED1.1.00/02.0073 Institutional support: RVO:67179843 Keywords : environmental chemistry * ebullition of methane * mixed poisson processes * renewal process * pareto distribution * moving average process * robust statistics * sedge–grass marsh Subject RIV: EH - Ecology, Behaviour Impact factor: 2.381, year: 2013
Directory of Open Access Journals (Sweden)
Dan S Bolintineanu
2009-01-01
Full Text Available Protegrin peptides are potent antimicrobial agents believed to act against a variety of pathogens by forming nonselective transmembrane pores in the bacterial cell membrane. We have employed 3D Poisson-Nernst-Planck (PNP calculations to determine the steady-state ion conduction characteristics of such pores at applied voltages in the range of -100 to +100 mV in 0.1 M KCl bath solutions. We have tested a variety of pore structures extracted from molecular dynamics (MD simulations based on an experimentally proposed octomeric pore structure. The computed single-channel conductance values were in the range of 290-680 pS. Better agreement with the experimental range of 40-360 pS was obtained using structures from the last 40 ns of the MD simulation, where conductance values range from 280 to 430 pS. We observed no significant variation of the conductance with applied voltage in any of the structures that we tested, suggesting that the voltage dependence observed experimentally is a result of voltage-dependent channel formation rather than an inherent feature of the open pore structure. We have found the pore to be highly selective for anions, with anionic to cationic current ratios (I(Cl-/I(K+ on the order of 10(3. This is consistent with the highly cationic nature of the pore but surprisingly in disagreement with the experimental finding of only slight anionic selectivity. We have additionally tested the sensitivity of our PNP model to several parameters and found the ion diffusion coefficients to have a significant influence on conductance characteristics. The best agreement with experimental data was obtained using a diffusion coefficient for each ion set to 10% of the bulk literature value everywhere inside the channel, a scaling used by several other studies employing PNP calculations. Overall, this work presents a useful link between previous work focused on the structure of protegrin pores and experimental efforts aimed at investigating their
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E.O. Ulloa-Dávila
2017-12-01
Full Text Available An approximate analytical solution to the fluctuation potential problem in the modified Poisson-Boltzmann theory of electrolyte solutions in the restricted primitive model is presented. The solution is valid for all inter-ionic distances, including contact values. The fluctuation potential solution is implemented in the theory to describe the structure of the electrolyte in terms of the radial distribution functions, and to calculate some aspects of thermodynamics, viz., configurational reduced energies, and osmotic coefficients. The calculations have been made for symmetric valence 1:1 systems at the physical parameters of ionic diameter 4.25·10^{-10} m, relative permittivity 78.5, absolute temperature 298 K, and molar concentrations 0.1038, 0.425, 1.00, and 1.968. Radial distribution functions are compared with the corresponding results from the symmetric Poisson-Boltzmann, and the conventional and modified Poisson-Boltzmann theories. Comparisons have also been done for the contact values of the radial distributions, reduced configurational energies, and osmotic coefficients as functions of electrolyte concentration. Some Monte Carlo simulation data from the literature are also included in the assessment of the thermodynamic predictions. Results show a very good agreement with the Monte Carlo results and some improvement for osmotic coefficients and radial distribution functions contact values relative to these theories. The reduced energy curve shows excellent agreement with Monte Carlo data for molarities up to 1 mol/dm^3.
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Muhammad Mohsin
2010-11-01
Full Text Available In this paper the Erlang-truncated exponential distribution is characterized by the conditional expectation of record values. The utility of our result is demonstrated in mean residual life by using this characterization.
Wang, Yiyi; Kockelman, Kara M
2013-11-01
This work examines the relationship between 3-year pedestrian crash counts across Census tracts in Austin, Texas, and various land use, network, and demographic attributes, such as land use balance, residents' access to commercial land uses, sidewalk density, lane-mile densities (by roadway class), and population and employment densities (by type). The model specification allows for region-specific heterogeneity, correlation across response types, and spatial autocorrelation via a Poisson-based multivariate conditional auto-regressive (CAR) framework and is estimated using Bayesian Markov chain Monte Carlo methods. Least-squares regression estimates of walk-miles traveled per zone serve as the exposure measure. Here, the Poisson-lognormal multivariate CAR model outperforms an aspatial Poisson-lognormal multivariate model and a spatial model (without cross-severity correlation), both in terms of fit and inference. Positive spatial autocorrelation emerges across neighborhoods, as expected (due to latent heterogeneity or missing variables that trend in space, resulting in spatial clustering of crash counts). In comparison, the positive aspatial, bivariate cross correlation of severe (fatal or incapacitating) and non-severe crash rates reflects latent covariates that have impacts across severity levels but are more local in nature (such as lighting conditions and local sight obstructions), along with spatially lagged cross correlation. Results also suggest greater mixing of residences and commercial land uses is associated with higher pedestrian crash risk across different severity levels, ceteris paribus, presumably since such access produces more potential conflicts between pedestrian and vehicle movements. Interestingly, network densities show variable effects, and sidewalk provision is associated with lower severe-crash rates. Copyright © 2013 Elsevier Ltd. All rights reserved.
An Erlang-like model using SDCCH dimensioning and reattempt ...
African Journals Online (AJOL)
Journal of Computer Science and Its Application. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 21, No 1 (2014) >. Log in or Register to get access to full text downloads.
Kyllingsbæk, Søren; Markussen, Bo; Bundesen, Claus
2012-06-01
The authors propose and test a simple model of the time course of visual identification of briefly presented, mutually confusable single stimuli in pure accuracy tasks. The model implies that during stimulus analysis, tentative categorizations that stimulus i belongs to category j are made at a constant Poisson rate, v(i, j). The analysis is continued until the stimulus disappears, and the overt response is based on the categorization made the greatest number of times. The model was evaluated by Monte Carlo tests of goodness of fit against observed probability distributions of responses in two extensive experiments and also by quantifications of the information loss of the model compared with the observed data by use of information theoretic measures. The model provided a close fit to individual data on identification of digits and an apparently perfect fit to data on identification of Landolt rings.
International Nuclear Information System (INIS)
Gao, Li-Na; Liu, Fu-Hu; Lacey, Roy A.
2016-01-01
Experimental results of the transverse-momentum distributions of φ mesons and Ω hyperons produced in gold-gold (Au-Au) collisions with different centrality intervals, measured by the STAR Collaboration at different energies (7.7, 11.5, 19.6, 27, and 39 GeV) in the beam energy scan (BES) program at the relativistic heavy-ion collider (RHIC), are approximately described by the single Erlang distribution and the two-component Schwinger mechanism. Moreover, the STAR experimental transverse-momentum distributions of negatively charged particles, produced in Au-Au collisions at RHIC BES energies, are approximately described by the two-component Erlang distribution and the single Tsallis statistics. The excitation functions of free parameters are obtained from the fit to the experimental data. A weak softest point in the string tension in Ω hyperon spectra is observed at 7.7 GeV. (orig.)
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Gao, Li-Na; Liu, Fu-Hu [Shanxi University, Institute of Theoretical Physics, Shanxi (China); Lacey, Roy A. [Stony Brook University, Departments of Chemistry and Physics, Stony Brook, NY (United States)
2016-05-15
Experimental results of the transverse-momentum distributions of φ mesons and Ω hyperons produced in gold-gold (Au-Au) collisions with different centrality intervals, measured by the STAR Collaboration at different energies (7.7, 11.5, 19.6, 27, and 39 GeV) in the beam energy scan (BES) program at the relativistic heavy-ion collider (RHIC), are approximately described by the single Erlang distribution and the two-component Schwinger mechanism. Moreover, the STAR experimental transverse-momentum distributions of negatively charged particles, produced in Au-Au collisions at RHIC BES energies, are approximately described by the two-component Erlang distribution and the single Tsallis statistics. The excitation functions of free parameters are obtained from the fit to the experimental data. A weak softest point in the string tension in Ω hyperon spectra is observed at 7.7 GeV. (orig.)
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Li-Na Gao
2016-01-01
Full Text Available We study the transverse momentum spectra of J/ψ and Υ mesons by using two methods: the two-component Erlang distribution and the two-component Schwinger mechanism. The results obtained by the two methods are compared and found to be in agreement with the experimental data of proton-proton (pp, proton-lead (p-Pb, and lead-lead (Pb-Pb collisions measured by the LHCb and ALICE Collaborations at the large hadron collider (LHC. The related parameters such as the mean transverse momentum contributed by each parton in the first (second component in the two-component Erlang distribution and the string tension between two partons in the first (second component in the two-component Schwinger mechanism are extracted.
Eliazar, Iddo; Klafter, Joseph
2008-05-01
Many random populations can be modeled as a countable set of points scattered randomly on the positive half-line. The points may represent magnitudes of earthquakes and tornados, masses of stars, market values of public companies, etc. In this article we explore a specific class of random such populations we coin ` Paretian Poisson processes'. This class is elemental in statistical physics—connecting together, in a deep and fundamental way, diverse issues including: the Poisson distribution of the Law of Small Numbers; Paretian tail statistics; the Fréchet distribution of Extreme Value Theory; the one-sided Lévy distribution of the Central Limit Theorem; scale-invariance, renormalization and fractality; resilience to random perturbations.
Poisson integrators for Lie-Poisson structures on R3
International Nuclear Information System (INIS)
Song Lina
2011-01-01
This paper is concerned with the study of Poisson integrators. We are interested in Lie-Poisson systems on R 3 . First, we focus on Poisson integrators for constant Poisson systems and the transformations used for transforming Lie-Poisson structures to constant Poisson structures. Then, we construct local Poisson integrators for Lie-Poisson systems on R 3 . Finally, we present the results of numerical experiments for two Lie-Poisson systems and compare our Poisson integrators with other known methods.
On the Linear Stability of Crystals in the Schrödinger-Poisson Model
Komech, A.; Kopylova, E.
2016-10-01
We consider the Schrödinger-Poisson-Newton equations for crystals with one ion per cell. We linearize this dynamics at the periodic minimizers of energy per cell and introduce a novel class of the ion charge densities that ensures the stability of the linearized dynamics. Our main result is the energy positivity for the Bloch generators of the linearized dynamics under a Wiener-type condition on the ion charge density. We also adopt an additional `Jellium' condition which cancels the negative contribution caused by the electrostatic instability and provides the `Jellium' periodic minimizers and the optimality of the lattice: the energy per cell of the periodic minimizer attains the global minimum among all possible lattices. We show that the energy positivity can fail if the Jellium condition is violated, while the Wiener condition holds. The proof of the energy positivity relies on a novel factorization of the corresponding Hamilton functional. The Bloch generators are nonselfadjoint (and even nonsymmetric) Hamilton operators. We diagonalize these generators using our theory of spectral resolution of the Hamilton operators with positive definite energy (Komech and Kopylova in, J Stat Phys 154(1-2):503-521, 2014, J Spectral Theory 5(2):331-361, 2015). The stability of the linearized crystal dynamics is established using this spectral resolution.
Islam, Mohammad Mafijul; Alam, Morshed; Tariquzaman, Md; Kabir, Mohammad Alamgir; Pervin, Rokhsona; Begum, Munni; Khan, Md Mobarak Hossain
2013-01-08
Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable. The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model. The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance variable namely mother's education, father's education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman. Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh.
Sadler, J. M.; Goodall, J. L.; Morsy, M. M.; Spencer, K.
2018-04-01
Sea level rise has already caused more frequent and severe coastal flooding and this trend will likely continue. Flood prediction is an essential part of a coastal city's capacity to adapt to and mitigate this growing problem. Complex coastal urban hydrological systems however, do not always lend themselves easily to physically-based flood prediction approaches. This paper presents a method for using a data-driven approach to estimate flood severity in an urban coastal setting using crowd-sourced data, a non-traditional but growing data source, along with environmental observation data. Two data-driven models, Poisson regression and Random Forest regression, are trained to predict the number of flood reports per storm event as a proxy for flood severity, given extensive environmental data (i.e., rainfall, tide, groundwater table level, and wind conditions) as input. The method is demonstrated using data from Norfolk, Virginia USA from September 2010 to October 2016. Quality-controlled, crowd-sourced street flooding reports ranging from 1 to 159 per storm event for 45 storm events are used to train and evaluate the models. Random Forest performed better than Poisson regression at predicting the number of flood reports and had a lower false negative rate. From the Random Forest model, total cumulative rainfall was by far the most dominant input variable in predicting flood severity, followed by low tide and lower low tide. These methods serve as a first step toward using data-driven methods for spatially and temporally detailed coastal urban flood prediction.
The Poisson aggregation process
International Nuclear Information System (INIS)
Eliazar, Iddo
2016-01-01
In this paper we introduce and analyze the Poisson Aggregation Process (PAP): a stochastic model in which a random collection of random balls is stacked over a general metric space. The scattering of the balls’ centers follows a general Poisson process over the metric space, and the balls’ radii are independent and identically distributed random variables governed by a general distribution. For each point of the metric space, the PAP counts the number of balls that are stacked over it. The PAP model is a highly versatile spatial counterpart of the temporal M/G/∞ model in queueing theory. The surface of the moon, scarred by circular meteor-impact craters, exemplifies the PAP model in two dimensions: the PAP counts the number of meteor-impacts that any given moon-surface point sustained. A comprehensive analysis of the PAP is presented, and the closed-form results established include: general statistics, stationary statistics, short-range and long-range dependencies, a Central Limit Theorem, an Extreme Limit Theorem, and fractality.
Chavanis, P H; Delfini, L
2014-03-01
We study random transitions between two metastable states that appear below a critical temperature in a one-dimensional self-gravitating Brownian gas with a modified Poisson equation experiencing a second order phase transition from a homogeneous phase to an inhomogeneous phase [P. H. Chavanis and L. Delfini, Phys. Rev. E 81, 051103 (2010)]. We numerically solve the N-body Langevin equations and the stochastic Smoluchowski-Poisson system, which takes fluctuations (finite N effects) into account. The system switches back and forth between the two metastable states (bistability) and the particles accumulate successively at the center or at the boundary of the domain. We explicitly show that these random transitions exhibit the phenomenology of the ordinary Kramers problem for a Brownian particle in a double-well potential. The distribution of the residence time is Poissonian and the average lifetime of a metastable state is given by the Arrhenius law; i.e., it is proportional to the exponential of the barrier of free energy ΔF divided by the energy of thermal excitation kBT. Since the free energy is proportional to the number of particles N for a system with long-range interactions, the lifetime of metastable states scales as eN and is considerable for N≫1. As a result, in many applications, metastable states of systems with long-range interactions can be considered as stable states. However, for moderate values of N, or close to a critical point, the lifetime of the metastable states is reduced since the barrier of free energy decreases. In that case, the fluctuations become important and the mean field approximation is no more valid. This is the situation considered in this paper. By an appropriate change of notations, our results also apply to bacterial populations experiencing chemotaxis in biology. Their dynamics can be described by a stochastic Keller-Segel model that takes fluctuations into account and goes beyond the usual mean field approximation.
Minois, Nathan; Lauwers-Cances, Valérie; Savy, Stéphanie; Attal, Michel; Andrieu, Sandrine; Anisimov, Vladimir; Savy, Nicolas
2017-10-15
At the design of clinical trial operation, a question of a paramount interest is how long it takes to recruit a given number of patients. Modelling the recruitment dynamics is the necessary step to answer this question. Poisson-gamma model provides very convenient, flexible and realistic approach. This model allows predicting the trial duration using data collected at an interim time with very good accuracy. A natural question arises: how to evaluate the parameters of recruitment model before the trial begins? The question is harder to handle as there are no recruitment data available for this trial. However, if there exist similar completed trials, it is appealing to use data from these trials to investigate feasibility of the recruitment process. In this paper, the authors explore the recruitment data of two similar clinical trials (Intergroupe Francais du Myélome 2005 and 2009). It is shown that the natural idea of plugging the historical rates estimated from the completed trial in the same centres of the new trial for predicting recruitment is not a relevant strategy. In contrast, using the parameters of a gamma distribution of the rates estimated from the completed trial in the recruitment dynamic model of the new trial provides reasonable predictive properties with relevant confidence intervals. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Grøn, Randi; Gerds, Thomas A; Andersen, Per K
2016-03-30
Poisson regression is an important tool in register-based epidemiology where it is used to study the association between exposure variables and event rates. In this paper, we will discuss the situation with 'large n and small p', where n is the sample size and p is the number of available covariates. Specifically, we are concerned with modeling options when there are time-varying covariates that can have time-varying effects. One problem is that tests of the proportional hazards assumption, of no interactions between exposure and other observed variables, or of other modeling assumptions have large power due to the large sample size and will often indicate statistical significance even for numerically small deviations that are unimportant for the subject matter. Another problem is that information on important confounders may be unavailable. In practice, this situation may lead to simple working models that are then likely misspecified. To support and improve conclusions drawn from such models, we discuss methods for sensitivity analysis, for estimation of average exposure effects using aggregated data, and a semi-parametric bootstrap method to obtain robust standard errors. The methods are illustrated using data from the Danish national registries investigating the diabetes incidence for individuals treated with antipsychotics compared with the general unexposed population. Copyright © 2015 John Wiley & Sons, Ltd.
Garcia, Jane Bernadette Denise M.; Esguerra, Jose Perico H.
2017-08-01
An approximate but closed-form expression for a Poisson-like steady state wealth distribution in a kinetic model of gambling was formulated from a finite number of its moments, which were generated from a βa,b(x) exchange distribution. The obtained steady-state wealth distributions have tails which are qualitatively similar to those observed in actual wealth distributions.
The asymptotic stability analysis in stochastic logistic model with Poisson growth coefficient
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Shaojuan Ma
2014-01-01
Full Text Available The asymptotic stability of a discrete logistic model with random growth coefficient is studied in this paper. Firstly, the discrete logistic model with random growth coefficient is built and reduced into its deterministic equivalent system by orthogonal polynomial approximation. Then, the linear stability theory and the Jury criterion of nonlinear deterministic discrete systems are applied to the equivalent one. At last, by mathematical analysis, we find that the parameter interval for asymptotic stability of nontrivial equilibrium in stochastic logistic system gets smaller as the random intensity or statistical parameters of random variable is increased and the random parameter's influence on asymptotic stability in stochastic logistic system becomes prominent.
Comparison of two generation-recombination terms in the Poisson-Nernst-Planck model
Energy Technology Data Exchange (ETDEWEB)
Lelidis, I. [Solid State Section, Department of Physics, University of Athens, Panepistimiopolis, Zografos, Athens 157 84 (Greece); Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino (Italy); Universite de Picardie Jules Verne, Laboratoire de Physique des Systemes Complexes, 33 rue Saint-Leu 80039, Amiens (France); Barbero, G. [Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino (Italy); Sfarna, A. [Solid State Section, Department of Physics, University of Athens, Panepistimiopolis, Zografos, Athens 157 84 (Greece)
2012-10-21
Two phenomenological forms proposed to take into account the generation-recombination phenomenon of ions are investigated. The first form models the phenomenon as a chemical reaction, containing two coefficients describing the dissociation of neutral particles in ions, and the recombination of ions to give neutral particles. The second form is based on the assumption that in thermodynamical equilibrium, a well-defined density of ions is stable. Any deviation from the equilibrium density gives rise to a source term proportional to the deviation, whose phenomenological coefficient plays the role of a life time. The analysis is performed by evaluating the electrical response of an electrolytic cell to an external stimulus for both forms. For simplicity we assume that the electrodes are blocking, that there is only a group of negative and positive ions, and that the negative ions are immobile. For the second form, two cases are considered: (i) the generation-recombination phenomenon is due to an intrinsic mechanism, and (ii) the production of ions is triggered by an external source of energy, as in a solar cell. We show that the predictions of the two models are different at the impedance as well as at the admittance level. In particular, the first model predicts the existence of two plateaux for the real part of the impedance, whereas the second one predicts just one. It follows that impedance spectroscopy measurements could give information on the model valid for the generation-recombination of ions.
A Multi-Model Stereo Similarity Function Based on Monogenic Signal Analysis in Poisson Scale Space
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Jinjun Li
2011-01-01
Full Text Available A stereo similarity function based on local multi-model monogenic image feature descriptors (LMFD is proposed to match interest points and estimate disparity map for stereo images. Local multi-model monogenic image features include local orientation and instantaneous phase of the gray monogenic signal, local color phase of the color monogenic signal, and local mean colors in the multiscale color monogenic signal framework. The gray monogenic signal, which is the extension of analytic signal to gray level image using Dirac operator and Laplace equation, consists of local amplitude, local orientation, and instantaneous phase of 2D image signal. The color monogenic signal is the extension of monogenic signal to color image based on Clifford algebras. The local color phase can be estimated by computing geometric product between the color monogenic signal and a unit reference vector in RGB color space. Experiment results on the synthetic and natural stereo images show the performance of the proposed approach.
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Fabyano Fonseca Silva
2011-01-01
Full Text Available Nowadays, an important and interesting alternative in the control of tick-infestation in cattle is to select resistant animals, and identify the respective quantitative trait loci (QTLs and DNA markers, for posterior use in breeding programs. The number of ticks/animal is characterized as a discrete-counting trait, which could potentially follow Poisson distribution. However, in the case of an excess of zeros, due to the occurrence of several noninfected animals, zero-inflated Poisson and generalized zero-inflated distribution (GZIP may provide a better description of the data. Thus, the objective here was to compare through simulation, Poisson and ZIP models (simple and generalized with classical approaches, for QTL mapping with counting phenotypes under different scenarios, and to apply these approaches to a QTL study of tick resistance in an F2 cattle (Gyr x Holstein population. It was concluded that, when working with zero-inflated data, it is recommendable to use the generalized and simple ZIP model for analysis. On the other hand, when working with data with zeros, but not zero-inflated, the Poisson model or a data-transformation-approach, such as square-root or Box-Cox transformation, are applicable.
Jones, Bleddyn
2009-06-01
Current technical radiotherapy advances aim to (a) better conform the dose contours to cancers and (b) reduce the integral dose exposure and thereby minimise unnecessary dose exposure to normal tissues unaffected by the cancer. Various types of conformal and intensity modulated radiotherapy (IMRT) using x-rays can achieve (a) while charged particle therapy (CPT)-using proton and ion beams-can achieve both (a) and (b), but at greater financial cost. Not only is the long term risk of radiation related normal tissue complications important, but so is the risk of carcinogenesis. Physical dose distribution plans can be generated to show the differences between the above techniques. IMRT is associated with a dose bath of low to medium dose due to fluence transfer: dose is effectively transferred from designated organs at risk to other areas; thus dose and risk are transferred. Many clinicians are concerned that there may be additional carcinogenesis many years after IMRT. CPT reduces the total energy deposition in the body and offers many potential advantages in terms of the prospects for better quality of life along with cancer cure. With C ions there is a tail of dose beyond the Bragg peaks, due to nuclear fragmentation; this is not found with protons. CPT generally uses higher linear energy transfer (which varies with particle and energy), which carries a higher relative risk of malignant induction, but also of cell death quantified by the relative biological effect concept, so at higher dose levels the frank development of malignancy should be reduced. Standard linear radioprotection models have been used to show a reduction in carcinogenesis risk of between two- and 15-fold depending on the CPT location. But the standard risk models make no allowance for fractionation and some have a dose limit at 4 Gy. Alternatively, tentative application of the linear quadratic model and Poissonian statistics to chromosome breakage and cell kill simultaneously allows estimation of
Starrfelt, Jostein; Liow, Lee Hsiang
2016-04-05
The fossil record is a rich source of information about biological diversity in the past. However, the fossil record is not only incomplete but has also inherent biases due to geological, physical, chemical and biological factors. Our knowledge of past life is also biased because of differences in academic and amateur interests and sampling efforts. As a result, not all individuals or species that lived in the past are equally likely to be discovered at any point in time or space. To reconstruct temporal dynamics of diversity using the fossil record, biased sampling must be explicitly taken into account. Here, we introduce an approach that uses the variation in the number of times each species is observed in the fossil record to estimate both sampling bias and true richness. We term our technique TRiPS (True Richness estimated using a Poisson Sampling model) and explore its robustness to violation of its assumptions via simulations. We then venture to estimate sampling bias and absolute species richness of dinosaurs in the geological stages of the Mesozoic. Using TRiPS, we estimate that 1936 (1543-2468) species of dinosaurs roamed the Earth during the Mesozoic. We also present improved estimates of species richness trajectories of the three major dinosaur clades: the sauropodomorphs, ornithischians and theropods, casting doubt on the Jurassic-Cretaceous extinction event and demonstrating that all dinosaur groups are subject to considerable sampling bias throughout the Mesozoic. © 2016 The Authors.
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Mahsa Saadati
2012-01-01
Full Text Available Background: Epilepsy is a common, chronic neurological disorder that affects more than 40 million people worldwide. Epilepsy is characterized by interictal and ictal functional disturbances. The presence of interictal epileptiform discharges (IEDs can help to confirm a clinical diagnosis of epilepsy, and their location and characteristics can help to identify the epileptogenic zone or suggest a particular epilepsy syndrome. The aim of this study is to determine the factors that affect IEDs. Materials and Methods: Poisson marginal model was done on 60 epileptic patients who were referred to Shefa Neurological Research Center, Tehran, for Video-Electroencephalogram (V-EEG monitoring from 2007 to 2011. The frequency of IEDs was assessed by visual analysis of interictal EEG samples for 2 h. Results: The results show that among age, epilepsy duration, gender, seizure frequency and two common anti-epileptic drugs (Valproic acid and Carbamazepine, only age and epilepsy duration had statistical significant effect on IED frequency. Conclusion: Investigating the factors affecting IED is not only of theoretical importance, but may also have clinical relevance as understanding the evolution of interictal epileptogenesis may lead to the development of therapeutic interventions. Generalized estimating equation is a valid statistical technique for studying factors that affect on IED. This research demonstrates epilepsy duration has positive and age has negative effect on IED which means that IED increases with epilepsy duration and decreases with increasing age. So for monitoring IED, we should consider both age and epilepsy duration of each patient.
Homogeneous Poisson structures
International Nuclear Information System (INIS)
Shafei Deh Abad, A.; Malek, F.
1993-09-01
We provide an algebraic definition for Schouten product and give a decomposition for any homogenenous Poisson structure in any n-dimensional vector space. A large class of n-homogeneous Poisson structures in R k is also characterized. (author). 4 refs
Fogolari, Federico; Corazza, Alessandra; Esposito, Gennaro
2015-04-05
The generalized Born model in the Onufriev, Bashford, and Case (Onufriev et al., Proteins: Struct Funct Genet 2004, 55, 383) implementation has emerged as one of the best compromises between accuracy and speed of computation. For simulations of nucleic acids, however, a number of issues should be addressed: (1) the generalized Born model is based on a linear model and the linearization of the reference Poisson-Boltmann equation may be questioned for highly charged systems as nucleic acids; (2) although much attention has been given to potentials, solvation forces could be much less sensitive to linearization than the potentials; and (3) the accuracy of the Onufriev-Bashford-Case (OBC) model for nucleic acids depends on fine tuning of parameters. Here, we show that the linearization of the Poisson Boltzmann equation has mild effects on computed forces, and that with optimal choice of the OBC model parameters, solvation forces, essential for molecular dynamics simulations, agree well with those computed using the reference Poisson-Boltzmann model. © 2015 Wiley Periodicals, Inc.
Ahdika, Atina; Lusiyana, Novyan
2017-02-01
World Health Organization (WHO) noted Indonesia as the country with the highest dengue (DHF) cases in Southeast Asia. There are no vaccine and specific treatment for DHF. One of the efforts which can be done by both government and resident is doing a prevention action. In statistics, there are some methods to predict the number of DHF cases to be used as the reference to prevent the DHF cases. In this paper, a discrete time series model, INAR(1)-Poisson model in specific, and Markov prediction model are used to predict the number of DHF patients in West Java Indonesia. The result shows that MPM is the best model since it has the smallest value of MAE (mean absolute error) and MAPE (mean absolute percentage error).
Zeroth Poisson Homology, Foliated Cohomology and Perfect Poisson Manifolds
Martínez-Torres, David; Miranda, Eva
2018-01-01
We prove that, for compact regular Poisson manifolds, the zeroth homology group is isomorphic to the top foliated cohomology group, and we give some applications. In particular, we show that, for regular unimodular Poisson manifolds, top Poisson and foliated cohomology groups are isomorphic. Inspired by the symplectic setting, we define what a perfect Poisson manifold is. We use these Poisson homology computations to provide families of perfect Poisson manifolds.
International Nuclear Information System (INIS)
Harwood, L.H.
1981-01-01
At MSU we have used the POISSON family of programs extensively for magnetic field calculations. In the presently super-saturated computer situation, reducing the run time for the program is imperative. Thus, a series of modifications have been made to POISSON to speed up convergence. Two of the modifications aim at having the first guess solution as close as possible to the final solution. The other two aim at increasing the convergence rate. In this discussion, a working knowledge of POISSON is assumed. The amount of new code and expected time saving for each modification is discussed
Scaling the Poisson Distribution
Farnsworth, David L.
2014-01-01
We derive the additive property of Poisson random variables directly from the probability mass function. An important application of the additive property to quality testing of computer chips is presented.
On Poisson Nonlinear Transformations
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Nasir Ganikhodjaev
2014-01-01
Full Text Available We construct the family of Poisson nonlinear transformations defined on the countable sample space of nonnegative integers and investigate their trajectory behavior. We have proved that these nonlinear transformations are regular.
Extended Poisson Exponential Distribution
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Anum Fatima
2015-09-01
Full Text Available A new mixture of Modified Exponential (ME and Poisson distribution has been introduced in this paper. Taking the Maximum of Modified Exponential random variable when the sample size follows a zero truncated Poisson distribution we have derived the new distribution, named as Extended Poisson Exponential distribution. This distribution possesses increasing and decreasing failure rates. The Poisson-Exponential, Modified Exponential and Exponential distributions are special cases of this distribution. We have also investigated some mathematical properties of the distribution along with Information entropies and Order statistics of the distribution. The estimation of parameters has been obtained using the Maximum Likelihood Estimation procedure. Finally we have illustrated a real data application of our distribution.
Poisson branching point processes
International Nuclear Information System (INIS)
Matsuo, K.; Teich, M.C.; Saleh, B.E.A.
1984-01-01
We investigate the statistical properties of a special branching point process. The initial process is assumed to be a homogeneous Poisson point process (HPP). The initiating events at each branching stage are carried forward to the following stage. In addition, each initiating event independently contributes a nonstationary Poisson point process (whose rate is a specified function) located at that point. The additional contributions from all points of a given stage constitute a doubly stochastic Poisson point process (DSPP) whose rate is a filtered version of the initiating point process at that stage. The process studied is a generalization of a Poisson branching process in which random time delays are permitted in the generation of events. Particular attention is given to the limit in which the number of branching stages is infinite while the average number of added events per event of the previous stage is infinitesimal. In the special case when the branching is instantaneous this limit of continuous branching corresponds to the well-known Yule--Furry process with an initial Poisson population. The Poisson branching point process provides a useful description for many problems in various scientific disciplines, such as the behavior of electron multipliers, neutron chain reactions, and cosmic ray showers
Lipsitz, Stuart R.; Parzen, Michael; Molenberghs, Geert
1998-01-01
This article describes estimation of the cell probabilities in an R x C contingency table with ignorable missing data. Popular methods for maximizing the incomplete data likelihood are the EM-algorithm and the Newton--Raphson algorithm. Both of these methods require some modification of existing statistical software to get the MLEs of the cell probabilities as well as the variance estimates. We make the connection between the multinomial and Poisson likelihoods to show that the MLEs can be ob...
Morrissey, M. L.
2009-12-01
A point process model for tropical rain rates is developed through the derivation of the third moment expression for a combined point process model. The model is a superposition of a Neyman-Scott rectangular pulse model and a Poisson white noise process model. The model is scalable in the temporal dimension. The derivation of the third moment for this model allows the inclusion of the skewness parameter which is necessary to adequately represent rainfall intensity. Analysis of the model fit to tropical tipping bucket raingauge data ranging in temporal scale from 5 minutes to one day indicates that it can adequately produce synthesized rainfall having the statistical characteristics of rain rate over the range of scales tested. Of special interest is the model’s capability to accurately preserve the probability of extreme tropical rain rates at different scales. In addition to various hydrological applications, the model also has many potential uses in the field of meteorology, such as the study and development of radar rain rate algorithms for the tropics which need to parameterized attenuation due to heavy rain.
Mani, Prashant; Tyagi, Chandra Shekhar; Srivastav, Nishant
2016-03-01
In this paper the analytical solution of the 2D Poisson's equation for single gate Fully Depleted SOI (FDSOI) MOSFET's is derived by using a Green's function solution technique. The surface potential is calculated and the threshold voltage of the device is minimized for the low power consumption. Due to minimization of threshold voltage the short channel effect of device is suppressed and after observation we obtain the device is kink free. The structure and characteristics of SingleGate FDSOI MOSFET were matched by using MathCAD and silvaco respectively.
Directory of Open Access Journals (Sweden)
H. D. Yin
2014-03-01
Full Text Available Cellular retinol-binding protein II (CRBP II belongs to the family of cellular retinol-binding proteins and plays a major role in absorption, transport, and metabolism of vitamin A. In addition, because vitamin A is correlated with reproductive performance, we measured CRBP II mRNA abundance in erlang mountainous chickens by real-time PCR using the relative quantification method. The expression of CRBP II showed a tissue-specific pattern and egg production rate-dependent changes. The expression was very high (p<0.05 in jejunum and liver, intermediate in kidney, ovary, and oviduct, and lowest (p<0.05 in heart, hypothalamus, and pituitary. In the hypothalamus, oviduct, ovary, and pituitary, CRBP II mRNA abundance were correlated to egg production rate, which increased from 12 wk to 32 wk, peaked at 32 wk relative to the other time points, and then decreased from 32 wk to 45 wk. In contrast, the expression of CRBP II mRNA in heart, jejunum, kidney, and liver was not different at any of the ages evaluated in this study. These data may help to understand the genetic basis of vitamin A metabolism, and suggest that CRBP II may be a candidate gene to affect egg production traits in chickens.
Calame, Jeffrey; Chernyavskiy, Igor; Ancona, Mario; Meyer, David
Polarization-gradient profiling of AlxGa1-xN/GaN heterostructures in the vertical (depth) direction, achieved by deliberate spatial tailoring of the aluminum concentration profile, can be used to control the spatial structure of the conducting electron gas in high electron mobility transistors. In particular, the typical two-dimensional electron gas of abrupt heterostructures can exhibit a more three-dimensional distribution in graded structures. This offers the possibility of improved device linearity through deliberate vertical heterostructure engineering, which can minimize or compensate for various scattering mechanisms that contribute to nonlinearity. Schrodinger-Poisson modeling (i.e., the Hartree approximation) is used to study the electron density profiles that result from such deliberate grading, and how those profiles evolve with the application of biasing vertical electric fields across the heterostructure. Implications of the results on device linearity will be discussed. Comparisons between the electron density profiles predicted by the Schrodinger-Poisson modeling and those obtained by density-gradient theory will be made in selected examples. Work supported by the U.S. Office of Naval Research.
DEFF Research Database (Denmark)
Andersen, Anders Holst; Korsgaard, Inge Riis; Jensen, Just
2002-01-01
In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed...
Wang, Chenggang; Jiang, Baofa; Fan, Jingchun; Wang, Furong; Liu, Qiyong
2014-01-01
The aim of this study is to develop a model that correctly identifies and quantifies the relationship between dengue and meteorological factors in Guangzhou, China. By cross-correlation analysis, meteorological variables and their lag effects were determined. According to the epidemic characteristics of dengue in Guangzhou, those statistically significant variables were modeled by a zero-inflated Poisson regression model. The number of dengue cases and minimum temperature at 1-month lag, along with average relative humidity at 0- to 1-month lag were all positively correlated with the prevalence of dengue fever, whereas wind velocity and temperature in the same month along with rainfall at 2 months' lag showed negative association with dengue incidence. Minimum temperature at 1-month lag and wind velocity in the same month had a greater impact on the dengue epidemic than other variables in Guangzhou.
Fractional Poisson Fields and Martingales
Aletti, Giacomo; Leonenko, Nikolai; Merzbach, Ely
2018-01-01
We present new properties for the Fractional Poisson process (FPP) and the Fractional Poisson field on the plane. A martingale characterization for FPPs is given. We extend this result to Fractional Poisson fields, obtaining some other characterizations. The fractional differential equations are studied. We consider a more general Mixed-Fractional Poisson process and show that this process is the stochastic solution of a system of fractional differential-difference equations. Finally, we give some simulations of the Fractional Poisson field on the plane.
Fractional Poisson Fields and Martingales
Aletti, Giacomo; Leonenko, Nikolai; Merzbach, Ely
2018-02-01
We present new properties for the Fractional Poisson process (FPP) and the Fractional Poisson field on the plane. A martingale characterization for FPPs is given. We extend this result to Fractional Poisson fields, obtaining some other characterizations. The fractional differential equations are studied. We consider a more general Mixed-Fractional Poisson process and show that this process is the stochastic solution of a system of fractional differential-difference equations. Finally, we give some simulations of the Fractional Poisson field on the plane.
Rusakov, Oleg; Laskin, Michael
2017-06-01
We consider a stochastic model of changes of prices in real estate markets. We suppose that in a book of prices the changes happen in points of jumps of a Poisson process with a random intensity, i.e. moments of changes sequently follow to a random process of the Cox process type. We calculate cumulative mathematical expectations and variances for the random intensity of this point process. In the case that the process of random intensity is a martingale the cumulative variance has a linear grows. We statistically process a number of observations of real estate prices and accept hypotheses of a linear grows for estimations as well for cumulative average, as for cumulative variance both for input and output prises that are writing in the book of prises.
Bijma, K; Engberts, J B F N
This paper describes how the theory of the ''dressed micelle'', which is based on the nonlinear Poisson-Boltzmann equation, can be used to calculate a number of thermodynamic quantities for micellization of sodium p-alkylbenzenesulphonates. From the Gibbs energy of micellization, the enthalpy of
Natural Poisson structures of nonlinear plasma dynamics
International Nuclear Information System (INIS)
Kaufman, A.N.
1982-06-01
Hamiltonian field theories, for models of nonlinear plasma dynamics, require a Poisson bracket structure for functionals of the field variables. These are presented, applied, and derived for several sets of field variables: coherent waves, incoherent waves, particle distributions, and multifluid electrodynamics. Parametric coupling of waves and plasma yields concise expressions for ponderomotive effects (in kinetic and fluid models) and for induced scattering
Natural Poisson structures of nonlinear plasma dynamics
International Nuclear Information System (INIS)
Kaufman, A.N.
1982-01-01
Hamiltonian field theories, for models of nonlinear plasma dynamics, require a Poisson bracket structure for functionals of the field variables. These are presented, applied, and derived for several sets of field variables: coherent waves, incoherent waves, particle distributions, and multifluid electrodynamics. Parametric coupling of waves and plasma yields concise expressions for ponderomotive effects (in kinetic and fluid models) and for induced scattering. (Auth.)
Estimation of Poisson noise in spatial domain
Švihlík, Jan; Fliegel, Karel; Vítek, Stanislav; Kukal, Jaromír.; Krbcová, Zuzana
2017-09-01
This paper deals with modeling of astronomical images in the spatial domain. We consider astronomical light images contaminated by the dark current which is modeled by Poisson random process. Dark frame image maps the thermally generated charge of the CCD sensor. In this paper, we solve the problem of an addition of two Poisson random variables. At first, the noise analysis of images obtained from the astronomical camera is performed. It allows estimating parameters of the Poisson probability mass functions in every pixel of the acquired dark frame. Then the resulting distributions of the light image can be found. If the distributions of the light image pixels are identified, then the denoising algorithm can be applied. The performance of the Bayesian approach in the spatial domain is compared with the direct approach based on the method of moments and the dark frame subtraction.
PENERAPAN REGRESI BINOMIAL NEGATIF UNTUK MENGATASI OVERDISPERSI PADA REGRESI POISSON
Directory of Open Access Journals (Sweden)
PUTU SUSAN PRADAWATI
2013-09-01
Full Text Available Poisson regression was used to analyze the count data which Poisson distributed. Poisson regression analysis requires state equidispersion, in which the mean value of the response variable is equal to the value of the variance. However, there are deviations in which the value of the response variable variance is greater than the mean. This is called overdispersion. If overdispersion happens and Poisson Regression analysis is being used, then underestimated standard errors will be obtained. Negative Binomial Regression can handle overdispersion because it contains a dispersion parameter. From the simulation data which experienced overdispersion in the Poisson Regression model it was found that the Negative Binomial Regression was better than the Poisson Regression model.
DEFF Research Database (Denmark)
Larsen, Christian; Kiesmüller, G.P
2007-01-01
We derive a closed-form cost expression for an (R,s,nQ) inventory control policy where all replenishment orders have a constant lead-time, unfilled demand is back-logged and inter-arrival times of order requests are generalized Erlang distributed. For given values of Q and R we show how to comput...
DEFF Research Database (Denmark)
Larsen, Christian; Kiesmüller, Gudrun P.
We derive a closed-form cost expression for an (R,s,nQ) inventory control policy where all replenishment orders have a constant lead-time, unfilled demand is backlogged and inter-arrival times of order requests are generalized Erlang distributed....
Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying
2016-01-01
Background Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic
Liao, Jiaqiang; Yu, Shicheng; Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying
2016-01-01
Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across
Franceries, X.; Doyon, B.; Chauveau, N.; Rigaud, B.; Celsis, P.; Morucci, J.-P.
2003-03-01
In electroencephalography (EEG) and event related potentials (ERP), localizing the electrical sources at the origin of scalp potentials (inverse problem) imposes, in a first step, the computation of scalp potential distribution from the simulation of sources (forward problem). This article proposes an alternative method for mimicing both the electrical and geometrical properties of the head, including brain, skull, and scalp tissue with resistors. Two resistor mesh models have been designed to reproduce the three-sphere reference model (analytical model). The first one (spherical resistor mesh) closely mimics the geometrical and electrical properties of the analytical model. The second one (cubic resistor mesh) is designed to conveniently handle anatomical data from magnetic resonance imaging. Both models have been validated, in reference to the analytical solution calculated on the three-sphere model, by computing the magnification factor and the relative difference measure. Results suggest that the mesh models can be used as robust and user-friendly simulation or exploration tools in EEG/ERP.
Madonna, Erica; Ginsbourger, David; Martius, Olivia
2018-05-01
In Switzerland, hail regularly causes substantial damage to agriculture, cars and infrastructure, however, little is known about its long-term variability. To study the variability, the monthly number of days with hail in northern Switzerland is modeled in a regression framework using large-scale predictors derived from ERA-Interim reanalysis. The model is developed and verified using radar-based hail observations for the extended summer season (April-September) in the period 2002-2014. The seasonality of hail is explicitly modeled with a categorical predictor (month) and monthly anomalies of several large-scale predictors are used to capture the year-to-year variability. Several regression models are applied and their performance tested with respect to standard scores and cross-validation. The chosen model includes four predictors: the monthly anomaly of the two meter temperature, the monthly anomaly of the logarithm of the convective available potential energy (CAPE), the monthly anomaly of the wind shear and the month. This model well captures the intra-annual variability and slightly underestimates its inter-annual variability. The regression model is applied to the reanalysis data back in time to 1980. The resulting hail day time series shows an increase of the number of hail days per month, which is (in the model) related to an increase in temperature and CAPE. The trend corresponds to approximately 0.5 days per month per decade. The results of the regression model have been compared to two independent data sets. All data sets agree on the sign of the trend, but the trend is weaker in the other data sets.
Poisson hierarchy of discrete strings
Energy Technology Data Exchange (ETDEWEB)
Ioannidou, Theodora, E-mail: ti3@auth.gr [Faculty of Civil Engineering, School of Engineering, Aristotle University of Thessaloniki, 54249, Thessaloniki (Greece); Niemi, Antti J., E-mail: Antti.Niemi@physics.uu.se [Department of Physics and Astronomy, Uppsala University, P.O. Box 803, S-75108, Uppsala (Sweden); Laboratoire de Mathematiques et Physique Theorique CNRS UMR 6083, Fédération Denis Poisson, Université de Tours, Parc de Grandmont, F37200, Tours (France); Department of Physics, Beijing Institute of Technology, Haidian District, Beijing 100081 (China)
2016-01-28
The Poisson geometry of a discrete string in three dimensional Euclidean space is investigated. For this the Frenet frames are converted into a spinorial representation, the discrete spinor Frenet equation is interpreted in terms of a transfer matrix formalism, and Poisson brackets are introduced in terms of the spinor components. The construction is then generalised, in a self-similar manner, into an infinite hierarchy of Poisson algebras. As an example, the classical Virasoro (Witt) algebra that determines reparametrisation diffeomorphism along a continuous string, is identified as a particular sub-algebra, in the hierarchy of the discrete string Poisson algebra. - Highlights: • Witt (classical Virasoro) algebra is derived in the case of discrete string. • Infinite dimensional hierarchy of Poisson bracket algebras is constructed for discrete strings. • Spinor representation of discrete Frenet equations is developed.
Poisson hierarchy of discrete strings
International Nuclear Information System (INIS)
Ioannidou, Theodora; Niemi, Antti J.
2016-01-01
The Poisson geometry of a discrete string in three dimensional Euclidean space is investigated. For this the Frenet frames are converted into a spinorial representation, the discrete spinor Frenet equation is interpreted in terms of a transfer matrix formalism, and Poisson brackets are introduced in terms of the spinor components. The construction is then generalised, in a self-similar manner, into an infinite hierarchy of Poisson algebras. As an example, the classical Virasoro (Witt) algebra that determines reparametrisation diffeomorphism along a continuous string, is identified as a particular sub-algebra, in the hierarchy of the discrete string Poisson algebra. - Highlights: • Witt (classical Virasoro) algebra is derived in the case of discrete string. • Infinite dimensional hierarchy of Poisson bracket algebras is constructed for discrete strings. • Spinor representation of discrete Frenet equations is developed.
DEFF Research Database (Denmark)
Paz-Garcia, Juan Manuel; Johannesson, Björn; Ottosen, Lisbeth M.
2011-01-01
equilibrium is continuously assured and the pH value is monitored. Results from some selected test simulations of the electrokinetic desalination of a sample of porous material are presented, outlining the versatility of the model as well as showing the effect of the counterion in the removal rate of a target...
Shimaponda-Mataa, Nzooma M; Tembo-Mwase, Enala; Gebreslasie, Michael; Achia, Thomas N O; Mukaratirwa, Samson
2017-11-01
Although malaria morbidity and mortality are greatly reduced globally owing to great control efforts, the disease remains the main contributor. In Zambia, all provinces are malaria endemic. However, the transmission intensities vary mainly depending on environmental factors as they interact with the vectors. Generally in Africa, possibly due to the varying perspectives and methods used, there is variation on the relative importance of malaria risk determinants. In Zambia, the role climatic factors play on malaria case rates has not been determined in combination of space and time using robust methods in modelling. This is critical considering the reversal in malaria reduction after the year 2010 and the variation by transmission zones. Using a geoadditive or structured additive semiparametric Poisson regression model, we determined the influence of climatic factors on malaria incidence in four endemic provinces of Zambia. We demonstrate a strong positive association between malaria incidence and precipitation as well as minimum temperature. The risk of malaria was 95% lower in Lusaka (ARR=0.05, 95% CI=0.04-0.06) and 68% lower in the Western Province (ARR=0.31, 95% CI=0.25-0.41) compared to Luapula Province. North-western Province did not vary from Luapula Province. The effects of geographical region are clearly demonstrated by the unique behaviour and effects of minimum and maximum temperatures in the four provinces. Environmental factors such as landscape in urbanised places may also be playing a role. Copyright © 2017 Elsevier B.V. All rights reserved.
Ghanta, Sindhu; Jordan, Michael I.; Kose, Kivanc; Brooks, Dana H.; Rajadhyaksha, Milind; Dy, Jennifer G.
2016-01-01
Segmenting objects of interest from 3D datasets is a common problem encountered in biological data. Small field of view and intrinsic biological variability combined with optically subtle changes of intensity, resolution and low contrast in images make the task of segmentation difficult, especially for microscopy of unstained living or freshly excised thick tissues. Incorporating shape information in addition to the appearance of the object of interest can often help improve segmentation performance. However, shapes of objects in tissue can be highly variable and design of a flexible shape model that encompasses these variations is challenging. To address such complex segmentation problems, we propose a unified probabilistic framework that can incorporate the uncertainty associated with complex shapes, variable appearance and unknown locations. The driving application which inspired the development of this framework is a biologically important segmentation problem: the task of automatically detecting and segmenting the dermal-epidermal junction (DEJ) in 3D reflectance confocal microscopy (RCM) images of human skin. RCM imaging allows noninvasive observation of cellular, nuclear and morphological detail. The DEJ is an important morphological feature as it is where disorder, disease and cancer usually start. Detecting the DEJ is challenging because it is a 2D surface in a 3D volume which has strong but highly variable number of irregularly spaced and variably shaped “peaks and valleys”. In addition, RCM imaging resolution, contrast and intensity vary with depth. Thus a prior model needs to incorporate the intrinsic structure while allowing variability in essentially all its parameters. We propose a model which can incorporate objects of interest with complex shapes and variable appearance in an unsupervised setting by utilizing domain knowledge to build appropriate priors of the model. Our novel strategy to model this structure combines a spatial Poisson process
Almasi-Hashiani, Amir; Mansournia, Mohammad Ali; Sepidarkish, Mahdi; Vesali, Samira; Ghaheri, Azadeh; Esmailzadeh, Arezoo; Omani-Samani, Reza
2018-01-01
Polycystic ovary syndrome (PCOS) is a frequent condition in reproductive age women with a prevalence rate of 5-10%. This study intends to determine the relationship between PCOS and the outcome of assisted reproductive treatment (ART) in Tehran, Iran. In this historical cohort study, we included 996 infertile women who referred to Royan Institute (Tehran, Iran) between January 2012 and December 2013. PCOS, as the main variable, and other potential confounder variables were gathered. Modified Poisson Regression was used for data analysis. Stata software, version 13 was used for all statistical analyses. Unadjusted analysis showed a significantly lower risk for failure in PCOS cases compared to cases without PCOS [risk ratio (RR): 0.79, 95% confidence intervals (CI): 0.66-0.95, P=0.014]. After adjusting for the confounder variables, there was no difference between risk of non-pregnancy in women with and without PCOS (RR: 0.87, 95% CI: 0.72-1.05, P=0.15). Significant predictors of the ART outcome included the treatment protocol type, numbers of embryos transferred (grades A and AB), numbers of injected ampules, and age. The results obtained from this model showed no difference between patients with and without PCOS according to the risk for non-pregnancy. Therefore, other factors might affect conception in PCOS patients. Copyright© by Royan Institute. All rights reserved.
Directory of Open Access Journals (Sweden)
L.B. Bhuiyan
2017-12-01
Full Text Available The modified Poisson-Boltzmann theory of the restricted primitive model double layer is revisited and recast in a fresh, slightly broader perspective. Derivation of relevant equations follow the techniques utilized in the earlier MPB4 and MPB5 formulations and clarifies the relationship between these. The MPB4, MPB5, and a new formulation of the theory are employed in an analysis of the structure and charge reversal phenomenon in asymmetric 2:1/1:2 valence electrolytes. Furthermore, polarization induced surface charge amplification is studied in 3:1/1:3 systems. The results are compared to the corresponding Monte Carlo simulations. The theories are seen to predict the "exact" simulation data to varying degrees of accuracy ranging from qualitative to almost quantitative. The results from a new version of the theory are found to be of comparable accuracy as the MPB5 results in many situations. However, in some cases involving low electrolyte concentrations, theoretical artifacts in the form of un-physical "shoulders" in the singlet ionic distribution functions are observed.
Analysis on Poisson and Gamma spaces
Kondratiev, Yuri; Silva, Jose Luis; Streit, Ludwig; Us, Georgi
1999-01-01
We study the spaces of Poisson, compound Poisson and Gamma noises as special cases of a general approach to non-Gaussian white noise calculus, see \\cite{KSS96}. We use a known unitary isomorphism between Poisson and compound Poisson spaces in order to transport analytic structures from Poisson space to compound Poisson space. Finally we study a Fock type structure of chaos decomposition on Gamma space.
Coordination of Conditional Poisson Samples
Directory of Open Access Journals (Sweden)
Grafström Anton
2015-12-01
Full Text Available Sample coordination seeks to maximize or to minimize the overlap of two or more samples. The former is known as positive coordination, and the latter as negative coordination. Positive coordination is mainly used for estimation purposes and to reduce data collection costs. Negative coordination is mainly performed to diminish the response burden of the sampled units. Poisson sampling design with permanent random numbers provides an optimum coordination degree of two or more samples. The size of a Poisson sample is, however, random. Conditional Poisson (CP sampling is a modification of the classical Poisson sampling that produces a fixed-size πps sample. We introduce two methods to coordinate Conditional Poisson samples over time or simultaneously. The first one uses permanent random numbers and the list-sequential implementation of CP sampling. The second method uses a CP sample in the first selection and provides an approximate one in the second selection because the prescribed inclusion probabilities are not respected exactly. The methods are evaluated using the size of the expected sample overlap, and are compared with their competitors using Monte Carlo simulation. The new methods provide a good coordination degree of two samples, close to the performance of Poisson sampling with permanent random numbers.
Poisson Plus Quantification for Digital PCR Systems.
Majumdar, Nivedita; Banerjee, Swapnonil; Pallas, Michael; Wessel, Thomas; Hegerich, Patricia
2017-08-29
Digital PCR, a state-of-the-art nucleic acid quantification technique, works by spreading the target material across a large number of partitions. The average number of molecules per partition is estimated using Poisson statistics, and then converted into concentration by dividing by partition volume. In this standard approach, identical partition sizing is assumed. Violations of this assumption result in underestimation of target quantity, when using Poisson modeling, especially at higher concentrations. The Poisson-Plus Model accommodates for this underestimation, if statistics of the volume variation are well characterized. The volume variation was measured on the chip array based QuantStudio 3D Digital PCR System using the ROX fluorescence level as a proxy for effective load volume per through-hole. Monte Carlo simulations demonstrate the efficacy of the proposed correction. Empirical measurement of model parameters characterizing the effective load volume on QuantStudio 3D Digital PCR chips is presented. The model was used to analyze digital PCR experiments and showed improved accuracy in quantification. At the higher concentrations, the modeling must take effective fill volume variation into account to produce accurate estimates. The extent of the difference from the standard to the new modeling is positively correlated to the extent of fill volume variation in the effective load of your reactions.
Travel Time Model for Right-Turning Vehicles of Secondary Street at Unsignalized Intersections
Directory of Open Access Journals (Sweden)
Feng Yu-Qin
2013-01-01
Full Text Available The travel time of right-turning vehicles on secondary street at unsignalized intersection is discussed in this paper. Under the assumption that the major-street through vehicles’ headway follows Erlang distribution and secondary-street right-turning vehicles’ headway follows Poisson distribution. The right-turning vehicles travel time model is established on the basis of gap theory and M/G/1 queue theory. Comparison is done with the common model based on the assumption that the major-street vehicles’ headway follows Poisson distribution. An intersection is selected to verify each model. The results show that the model established in this paper has stronger applicability, and its most relative error is less than 15%. In addition, the sensitivity analysis has been done. The results show that right-turning flow rate and major-street flow rate have a significant impact on the travel time. Hence, the methodology for travel time of right-turning vehicles at unsignalized intersection proposed in this paper is effective and applicable.
Analysis of overdispersed count data by mixtures of Poisson variables and Poisson processes.
Hougaard, P; Lee, M L; Whitmore, G A
1997-12-01
Count data often show overdispersion compared to the Poisson distribution. Overdispersion is typically modeled by a random effect for the mean, based on the gamma distribution, leading to the negative binomial distribution for the count. This paper considers a larger family of mixture distributions, including the inverse Gaussian mixture distribution. It is demonstrated that it gives a significantly better fit for a data set on the frequency of epileptic seizures. The same approach can be used to generate counting processes from Poisson processes, where the rate or the time is random. A random rate corresponds to variation between patients, whereas a random time corresponds to variation within patients.
Background stratified Poisson regression analysis of cohort data.
Richardson, David B; Langholz, Bryan
2012-03-01
Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.
Background stratified Poisson regression analysis of cohort data
International Nuclear Information System (INIS)
Richardson, David B.; Langholz, Bryan
2012-01-01
Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models. (orig.)
Background stratified Poisson regression analysis of cohort data
Energy Technology Data Exchange (ETDEWEB)
Richardson, David B. [University of North Carolina at Chapel Hill, Department of Epidemiology, School of Public Health, Chapel Hill, NC (United States); Langholz, Bryan [Keck School of Medicine, University of Southern California, Division of Biostatistics, Department of Preventive Medicine, Los Angeles, CA (United States)
2012-03-15
Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models. (orig.)
A comparison of Poisson-one-inflated power series distributions for ...
African Journals Online (AJOL)
A class of Poisson-one-inflated power series distributions (the binomial, the Poisson, the negative binomial, the geometric, the log-series and the misrecorded Poisson) are proposed for modeling rural out-migration at the household level. The probability mass functions of the mixture distributions are derived and fitted to the ...
DEFF Research Database (Denmark)
Nielsen, Carsten Søren; Kyllingsbæk, Søren; Markussen, Bo
2015-01-01
, pp. 628–642. http://dx.doi.org/10.1037/a0024751) used a computational shortcut (Equation A5) that strongly reduced the time needed to fit the Poisson counter model to experimental data. Unfortunately, the computational shortcut built on an approximation that was not well-founded in the Poisson...... is not well-founded, and reports the refits, as well as a proposal for a well-founded computational shortcut can be found at http://dx.doi.org/10.1037/xhp0000037.supp We are grateful to Carsten S. Nielsen for bringing this point to our attention and for working with the authors of this article to prepare...
Boundary Lax pairs from non-ultra-local Poisson algebras
International Nuclear Information System (INIS)
Avan, Jean; Doikou, Anastasia
2009-01-01
We consider non-ultra-local linear Poisson algebras on a continuous line. Suitable combinations of representations of these algebras yield representations of novel generalized linear Poisson algebras or 'boundary' extensions. They are parametrized by a boundary scalar matrix and depend, in addition, on the choice of an antiautomorphism. The new algebras are the classical-linear counterparts of the known quadratic quantum boundary algebras. For any choice of parameters, the non-ultra-local contribution of the original Poisson algebra disappears. We also systematically construct the associated classical Lax pair. The classical boundary principal chiral model is examined as a physical example.
Directory of Open Access Journals (Sweden)
Jensen Just
2002-05-01
Full Text Available Abstract In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed or random effects. In the different models, expressions are given (when these can be found – otherwise unbiased estimates are given for prediction error variance, accuracy of selection and expected response to selection on the additive genetic scale and on the observed scale. The expressions given for non Gaussian traits are generalisations of the well-known formulas for Gaussian traits – and reflect, for Poisson mixed models and frailty models for survival data, the hierarchal structure of the models. In general the ratio of the additive genetic variance to the total variance in the Gaussian part of the model (heritability on the normally distributed level of the model or a generalised version of heritability plays a central role in these formulas.
Graded geometry and Poisson reduction
Cattaneo, A S; Zambon, M
2009-01-01
The main result of [2] extends the Marsden-Ratiu reduction theorem [4] in Poisson geometry, and is proven by means of graded geometry. In this note we provide the background material about graded geometry necessary for the proof in [2]. Further, we provide an alternative algebraic proof for the main result. ©2009 American Institute of Physics
Poisson structure of the equations of ideal multispecies fluid electrodynamics
International Nuclear Information System (INIS)
Spencer, R.G.
1984-01-01
The equations of the two- (or multi-) fluid model of plasma physics are recast in Hamiltonian form, following general methods of symplectic geometry. The dynamical variables are the fields of physical interest, but are noncanonical, so that the Poisson bracket in the theory is not the standard one. However, it is a skew-symmetric bilinear form which, from the method of derivation, automatically satisfies the Jacobi identity; therefore, this noncanonical structure has all the essential properties of a canonical Poisson bracket
On the poisson's ratio of the nucleus pulposus.
Farrell, M D; Riches, P E
2013-10-01
Existing experimental data on the Poisson's ratio of nucleus pulposus (NP) tissue is limited. This study aims to determine whether the Poisson's ratio of NP tissue is strain-dependent, strain-rate-dependent, or varies with axial location in the disk. Thirty-two cylindrical plugs of bovine tail NP tissue were subjected to ramp-hold unconfined compression to 20% axial strain in 5% increments, at either 30 μm/s or 0.3 μm/s ramp speeds and the radial displacement determined using biaxial video extensometry. Following radial recoil, the true Poisson's ratio of the solid phase of NP tissue increased linearly with increasing strain and demonstrated strain-rate dependency. The latter finding suggests that the solid matrix undergoes stress relaxation during the test. For small strains, we suggest a Poisson's ratio of 0.125 to be used in biphasic models of the intervertebral disk.
Independent production and Poisson distribution
International Nuclear Information System (INIS)
Golokhvastov, A.I.
1994-01-01
The well-known statement of factorization of inclusive cross-sections in case of independent production of particles (or clusters, jets etc.) and the conclusion of Poisson distribution over their multiplicity arising from it do not follow from the probability theory in any way. Using accurately the theorem of the product of independent probabilities, quite different equations are obtained and no consequences relative to multiplicity distributions are obtained. 11 refs
Perturbation-induced emergence of Poisson-like behavior in non-Poisson systems
International Nuclear Information System (INIS)
Akin, Osman C; Grigolini, Paolo; Paradisi, Paolo
2009-01-01
The response of a system with ON–OFF intermittency to an external harmonic perturbation is discussed. ON–OFF intermittency is described by means of a sequence of random events, i.e., the transitions from the ON to the OFF state and vice versa. The unperturbed waiting times (WTs) between two events are assumed to satisfy a renewal condition, i.e., the WTs are statistically independent random variables. The response of a renewal model with non-Poisson ON–OFF intermittency, associated with non-exponential WT distribution, is analyzed by looking at the changes induced in the WT statistical distribution by the harmonic perturbation. The scaling properties are also studied by means of diffusion entropy analysis. It is found that, in the range of fast and relatively strong perturbation, the non-Poisson system displays a Poisson-like behavior in both WT distribution and scaling. In particular, the histogram of perturbed WTs becomes a sequence of equally spaced peaks, with intensity decaying exponentially in time. Further, the diffusion entropy detects an ordinary scaling (related to normal diffusion) instead of the expected unperturbed anomalous scaling related to the inverse power-law decay. Thus, an analysis based on the WT histogram and/or on scaling methods has to be considered with some care when dealing with perturbed intermittent systems
Comparison between two bivariate Poisson distributions through the ...
African Journals Online (AJOL)
To remedy this problem, Berkhout and Plug proposed a bivariate Poisson distribution accepting the correlation as well negative, equal to zero, that positive. In this paper, we show that these models are nearly everywhere asymptotically equal. From this survey that the ø-divergence converges toward zero, both models are ...
Parasites et parasitoses des poissons
De Kinkelin, Pierre; Morand, Marc; Hedrick, Ronald; Michel, Christian
2014-01-01
Cet ouvrage, richement illustré, offre un panorama représentatif des agents parasitaires rencontrés chez les poissons. S'appuyant sur les nouvelles conceptions de la classification phylogénétique, il met l'accent sur les propriétés biologiques, l'épidémiologie et les conséquences cliniques des groupes d'organismes en cause, à la lumière des avancées cognitives permises par les nouveaux outils de la biologie. Il est destiné à un large public, allant du monde de l'aquaculture à ceux de la santé...
Dualizing the Poisson summation formula.
Duffin, R J; Weinberger, H F
1991-01-01
If f(x) and g(x) are a Fourier cosine transform pair, then the Poisson summation formula can be written as 2sumfrominfinityn = 1g(n) + g(0) = 2sumfrominfinityn = 1f(n) + f(0). The concepts of linear transformation theory lead to the following dual of this classical relation. Let phi(x) and gamma(x) = phi(1/x)/x have absolutely convergent integrals over the positive real line. Let F(x) = sumfrominfinityn = 1phi(n/x)/x - integralinfinity0phi(t)dt and G(x) = sumfrominfinityn = 1gamma (n/x)/x - integralinfinity0 gamma(t)dt. Then F(x) and G(x) are a Fourier cosine transform pair. We term F(x) the "discrepancy" of phi because it is the error in estimating the integral phi of by its Riemann sum with the constant mesh spacing 1/x. PMID:11607208
Singular reduction of Nambu-Poisson manifolds
Das, Apurba
The version of Marsden-Ratiu Poisson reduction theorem for Nambu-Poisson manifolds by a regular foliation have been studied by Ibáñez et al. In this paper, we show that this reduction procedure can be extended to the singular case. Under a suitable notion of Hamiltonian flow on the reduced space, we show that a set of Hamiltonians on a Nambu-Poisson manifold can also be reduced.
Poisson-Fermi Formulation of Nonlocal Electrostatics in Electrolyte Solutions
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Liu Jinn-Liang
2017-10-01
Full Text Available We present a nonlocal electrostatic formulation of nonuniform ions and water molecules with interstitial voids that uses a Fermi-like distribution to account for steric and correlation efects in electrolyte solutions. The formulation is based on the volume exclusion of hard spheres leading to a steric potential and Maxwell’s displacement field with Yukawa-type interactions resulting in a nonlocal electric potential. The classical Poisson-Boltzmann model fails to describe steric and correlation effects important in a variety of chemical and biological systems, especially in high field or large concentration conditions found in and near binding sites, ion channels, and electrodes. Steric effects and correlations are apparent when we compare nonlocal Poisson-Fermi results to Poisson-Boltzmann calculations in electric double layer and to experimental measurements on the selectivity of potassium channels for K+ over Na+.
Thinning spatial point processes into Poisson processes
DEFF Research Database (Denmark)
Møller, Jesper; Schoenberg, Frederic Paik
This paper describes methods for randomly thinning certain classes of spatial point processes. In the case of a Markov point process, the proposed method involves a dependent thinning of a spatial birth-and-death process, where clans of ancestors associated with the original points are identified......, and where one simulates backwards and forwards in order to obtain the thinned process. In the case of a Cox process, a simple independent thinning technique is proposed. In both cases, the thinning results in a Poisson process if and only if the true Papangelou conditional intensity is used, and thus can...... be used as a diagnostic for assessing the goodness-of-fit of a spatial point process model. Several examples, including clustered and inhibitive point processes, are considered....
Thinning spatial point processes into Poisson processes
DEFF Research Database (Denmark)
Møller, Jesper; Schoenberg, Frederic Paik
2010-01-01
In this paper we describe methods for randomly thinning certain classes of spatial point processes. In the case of a Markov point process, the proposed method involves a dependent thinning of a spatial birth-and-death process, where clans of ancestors associated with the original points...... are identified, and where we simulate backwards and forwards in order to obtain the thinned process. In the case of a Cox process, a simple independent thinning technique is proposed. In both cases, the thinning results in a Poisson process if and only if the true Papangelou conditional intensity is used, and......, thus, can be used as a graphical exploratory tool for inspecting the goodness-of-fit of a spatial point process model. Several examples, including clustered and inhibitive point processes, are considered....
Associative and Lie deformations of Poisson algebras
Remm, Elisabeth
2011-01-01
Considering a Poisson algebra as a non associative algebra satisfying the Markl-Remm identity, we study deformations of Poisson algebras as deformations of this non associative algebra. This gives a natural interpretation of deformations which preserves the underlying associative structure and we study deformations which preserve the underlying Lie algebra.
Poisson Regression Analysis of Illness and Injury Surveillance Data
Energy Technology Data Exchange (ETDEWEB)
Frome E.L., Watkins J.P., Ellis E.D.
2012-12-12
The Department of Energy (DOE) uses illness and injury surveillance to monitor morbidity and assess the overall health of the work force. Data collected from each participating site include health events and a roster file with demographic information. The source data files are maintained in a relational data base, and are used to obtain stratified tables of health event counts and person time at risk that serve as the starting point for Poisson regression analysis. The explanatory variables that define these tables are age, gender, occupational group, and time. Typical response variables of interest are the number of absences due to illness or injury, i.e., the response variable is a count. Poisson regression methods are used to describe the effect of the explanatory variables on the health event rates using a log-linear main effects model. Results of fitting the main effects model are summarized in a tabular and graphical form and interpretation of model parameters is provided. An analysis of deviance table is used to evaluate the importance of each of the explanatory variables on the event rate of interest and to determine if interaction terms should be considered in the analysis. Although Poisson regression methods are widely used in the analysis of count data, there are situations in which over-dispersion occurs. This could be due to lack-of-fit of the regression model, extra-Poisson variation, or both. A score test statistic and regression diagnostics are used to identify over-dispersion. A quasi-likelihood method of moments procedure is used to evaluate and adjust for extra-Poisson variation when necessary. Two examples are presented using respiratory disease absence rates at two DOE sites to illustrate the methods and interpretation of the results. In the first example the Poisson main effects model is adequate. In the second example the score test indicates considerable over-dispersion and a more detailed analysis attributes the over-dispersion to extra-Poisson
Multi-parameter full waveform inversion using Poisson
Oh, Juwon
2016-07-21
In multi-parameter full waveform inversion (FWI), the success of recovering each parameter is dependent on characteristics of the partial derivative wavefields (or virtual sources), which differ according to parameterisation. Elastic FWIs based on the two conventional parameterisations (one uses Lame constants and density; the other employs P- and S-wave velocities and density) have low resolution of gradients for P-wave velocities (or ). Limitations occur because the virtual sources for P-wave velocity or (one of the Lame constants) are related only to P-P diffracted waves, and generate isotropic explosions, which reduce the spatial resolution of the FWI for these parameters. To increase the spatial resolution, we propose a new parameterisation using P-wave velocity, Poisson\\'s ratio, and density for frequency-domain multi-parameter FWI for isotropic elastic media. By introducing Poisson\\'s ratio instead of S-wave velocity, the virtual source for the P-wave velocity generates P-S and S-S diffracted waves as well as P-P diffracted waves in the partial derivative wavefields for the P-wave velocity. Numerical examples of the cross-triangle-square (CTS) model indicate that the new parameterisation provides highly resolved descent directions for the P-wave velocity. Numerical examples of noise-free and noisy data synthesised for the elastic Marmousi-II model support the fact that the new parameterisation is more robust for noise than the two conventional parameterisations.
Constructions and classifications of projective Poisson varieties
Pym, Brent
2018-03-01
This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.
Seasonally adjusted birth frequencies follow the Poisson distribution.
Barra, Mathias; Lindstrøm, Jonas C; Adams, Samantha S; Augestad, Liv A
2015-12-15
Variations in birth frequencies have an impact on activity planning in maternity wards. Previous studies of this phenomenon have commonly included elective births. A Danish study of spontaneous births found that birth frequencies were well modelled by a Poisson process. Somewhat unexpectedly, there were also weekly variations in the frequency of spontaneous births. Another study claimed that birth frequencies follow the Benford distribution. Our objective was to test these results. We analysed 50,017 spontaneous births at Akershus University Hospital in the period 1999-2014. To investigate the Poisson distribution of these births, we plotted their variance over a sliding average. We specified various Poisson regression models, with the number of births on a given day as the outcome variable. The explanatory variables included various combinations of years, months, days of the week and the digit sum of the date. The relationship between the variance and the average fits well with an underlying Poisson process. A Benford distribution was disproved by a goodness-of-fit test (p variables is significantly improved (p variable. Altogether 7.5% more children are born on Tuesdays than on Sundays. The digit sum of the date is non-significant as an explanatory variable (p = 0.23), nor does it increase the explained variance. INERPRETATION: Spontaneous births are well modelled by a time-dependent Poisson process when monthly and day-of-the-week variation is included. The frequency is highest in summer towards June and July, Friday and Tuesday stand out as particularly busy days, and the activity level is at its lowest during weekends.
Directory of Open Access Journals (Sweden)
Hasan ŞAHİN
2002-01-01
Full Text Available This study applies a Poisson regression model to annual Turkish strikes data of the period of 1964-1998. The Poisson regression model is preferable when the dependent variable is count data. Economical and social variables are used as determinants of the number of strikes. Empirical results show that the unemployment rate and a dummy variable that takes 0 before 1980 1 otherwise are significantly affects the number of strikes.
The Poisson equation on Klein surfaces
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Monica Rosiu
2016-04-01
Full Text Available We obtain a formula for the solution of the Poisson equation with Dirichlet boundary condition on a region of a Klein surface. This formula reveals the symmetric character of the solution.
Poisson point processes imaging, tracking, and sensing
Streit, Roy L
2010-01-01
This overview of non-homogeneous and multidimensional Poisson point processes and their applications features mathematical tools and applications from emission- and transmission-computed tomography to multiple target tracking and distributed sensor detection.
Poisson's ratio and Young's modulus of lipid bilayers in different phases
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Tayebeh eJadidi
2014-04-01
Full Text Available A general computational method is introduced to estimate the Poisson's ratio for membranes with small thickness.In this method, the Poisson's ratio is calculated by utilizing a rescaling of inter-particle distancesin one lateral direction under periodic boundary conditions. As an example for the coarse grained lipid model introduced by Lenz and Schmid, we calculate the Poisson's ratio in the gel, fluid, and interdigitated phases. Having the Poisson's ratio, enable us to obtain the Young's modulus for the membranes in different phases. The approach may be applied to other membranes such as graphene and tethered membranes in orderto predict the temperature dependence of its Poisson's ratio and Young's modulus.
Poisson structure of dynamical systems with three degrees of freedom
Gümral, Hasan; Nutku, Yavuz
1993-12-01
It is shown that the Poisson structure of dynamical systems with three degrees of freedom can be defined in terms of an integrable one-form in three dimensions. Advantage is taken of this fact and the theory of foliations is used in discussing the geometrical structure underlying complete and partial integrability. Techniques for finding Poisson structures are presented and applied to various examples such as the Halphen system which has been studied as the two-monopole problem by Atiyah and Hitchin. It is shown that the Halphen system can be formulated in terms of a flat SL(2,R)-valued connection and belongs to a nontrivial Godbillon-Vey class. On the other hand, for the Euler top and a special case of three-species Lotka-Volterra equations which are contained in the Halphen system as limiting cases, this structure degenerates into the form of globally integrable bi-Hamiltonian structures. The globally integrable bi-Hamiltonian case is a linear and the SL(2,R) structure is a quadratic unfolding of an integrable one-form in 3+1 dimensions. It is shown that the existence of a vector field compatible with the flow is a powerful tool in the investigation of Poisson structure and some new techniques for incorporating arbitrary constants into the Poisson one-form are presented herein. This leads to some extensions, analogous to q extensions, of Poisson structure. The Kermack-McKendrick model and some of its generalizations describing the spread of epidemics, as well as the integrable cases of the Lorenz, Lotka-Volterra, May-Leonard, and Maxwell-Bloch systems admit globally integrable bi-Hamiltonian structure.
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Darko Medved
2015-01-01
Full Text Available With the introduction of Solvency II a consistent market approach to the valuation of insurance assets and liabilities is required. For the best estimate of life annuity provisions one should estimate the longevity risk of the insured population in Slovenia. In this paper the current minimum standard in Slovenia for calculating pension annuities is tested using the Lee-Carter model. In particular, the mortality of the Slovenian population is projected using the best fit from the stochastic mortality projections method. The projected mortality statistics are then corrected with the selection effect and compared with the current minimum standard.
A dictionary learning approach for Poisson image deblurring.
Ma, Liyan; Moisan, Lionel; Yu, Jian; Zeng, Tieyong
2013-07-01
The restoration of images corrupted by blur and Poisson noise is a key issue in medical and biological image processing. While most existing methods are based on variational models, generally derived from a maximum a posteriori (MAP) formulation, recently sparse representations of images have shown to be efficient approaches for image recovery. Following this idea, we propose in this paper a model containing three terms: a patch-based sparse representation prior over a learned dictionary, the pixel-based total variation regularization term and a data-fidelity term capturing the statistics of Poisson noise. The resulting optimization problem can be solved by an alternating minimization technique combined with variable splitting. Extensive experimental results suggest that in terms of visual quality, peak signal-to-noise ratio value and the method noise, the proposed algorithm outperforms state-of-the-art methods.
Investigation of Random Switching Driven by a Poisson Point Process
DEFF Research Database (Denmark)
Simonsen, Maria; Schiøler, Henrik; Leth, John-Josef
2015-01-01
This paper investigates the switching mechanism of a two-dimensional switched system, when the switching events are generated by a Poisson point process. A model, in the shape of a stochastic process, for such a system is derived and the distribution of the trajectory's position is developed...... together with marginal density functions for the coordinate functions. Furthermore, the joint probability distribution is given explicitly....
Events in time: Basic analysis of Poisson data
Energy Technology Data Exchange (ETDEWEB)
Engelhardt, M.E.
1994-09-01
The report presents basic statistical methods for analyzing Poisson data, such as the member of events in some period of time. It gives point estimates, confidence intervals, and Bayesian intervals for the rate of occurrence per unit of time. It shows how to compare subsets of the data, both graphically and by statistical tests, and how to look for trends in time. It presents a compound model when the rate of occurrence varies randomly. Examples and SAS programs are given.
Gonzales-Barron, Ursula; Zwietering, Marcel H; Butler, Francis
2013-02-01
This study proposes a novel step-wise methodology for the derivation of a sampling plan by variables for food production systems characterised by relatively low concentrations of the inspected microorganism. After representing the universe of contaminated batches by modelling the between-batch and within-batch variability in microbial counts, a tolerance criterion defining batch acceptability (i.e., up to a tolerance percentage of the food units having microbial concentrations lower or equal to a critical concentration) is established to delineate a limiting quality contour that separates satisfactory from unsatisfactory batches. The problem consists then of finding the optimum decision criterion - arithmetic mean of the analytical results (microbiological limit, m(L)) and the sample size (n) - that satisfies a pre-defined level of confidence measured on the samples' mean distributions from all possible true within-batch distributions. This is approached by obtaining decision landscape curves representing collectively the conditional and joint producer's and consumer's risks at different microbiological limits along with confidence intervals representing uncertainty due to the propagated between-batch variability. Whilst the method requires a number of risk management decisions to be made such as the objective of the sampling plan (GMP-based or risk-based), the modality of derivation, the tolerance criterion or level of safety, and the statistical level of confidence, the proposed method can be used when past monitoring data are available so as to produce statistically-sound dynamic sampling plans with optimised efficiency and discriminatory power. For the illustration of Enterobacteriaceae concentrations on Irish sheep carcasses, a sampling regime of n=10 and m(L)=17.5CFU/cm(2) is recommended to ensure that the producer has at least a 90% confidence of accepting a satisfactory batch whilst the consumer at least a 97.5% confidence that a batch will not be
A generalized Poisson solver for first-principles device simulations
Energy Technology Data Exchange (ETDEWEB)
Bani-Hashemian, Mohammad Hossein; VandeVondele, Joost, E-mail: joost.vandevondele@mat.ethz.ch [Nanoscale Simulations, ETH Zürich, 8093 Zürich (Switzerland); Brück, Sascha; Luisier, Mathieu [Integrated Systems Laboratory, ETH Zürich, 8092 Zürich (Switzerland)
2016-01-28
Electronic structure calculations of atomistic systems based on density functional theory involve solving the Poisson equation. In this paper, we present a plane-wave based algorithm for solving the generalized Poisson equation subject to periodic or homogeneous Neumann conditions on the boundaries of the simulation cell and Dirichlet type conditions imposed at arbitrary subdomains. In this way, source, drain, and gate voltages can be imposed across atomistic models of electronic devices. Dirichlet conditions are enforced as constraints in a variational framework giving rise to a saddle point problem. The resulting system of equations is then solved using a stationary iterative method in which the generalized Poisson operator is preconditioned with the standard Laplace operator. The solver can make use of any sufficiently smooth function modelling the dielectric constant, including density dependent dielectric continuum models. For all the boundary conditions, consistent derivatives are available and molecular dynamics simulations can be performed. The convergence behaviour of the scheme is investigated and its capabilities are demonstrated.
High order Poisson Solver for unbounded flows
DEFF Research Database (Denmark)
Hejlesen, Mads Mølholm; Rasmussen, Johannes Tophøj; Chatelain, Philippe
2015-01-01
This paper presents a high order method for solving the unbounded Poisson equation on a regular mesh using a Green’s function solution. The high order convergence was achieved by formulating mollified integration kernels, that were derived from a filter regularisation of the solution field...... the equations of fluid mechanics as an example, but can be used in many physical problems to solve the Poisson equation on a rectangular unbounded domain. For the two-dimensional case we propose an infinitely smooth test function which allows for arbitrary high order convergence. Using Gaussian smoothing....... The method was implemented on a rectangular domain using fast Fourier transforms (FFT) to increase computational efficiency. The Poisson solver was extended to directly solve the derivatives of the solution. This is achieved either by including the differential operator in the integration kernel...
Selective Contrast Adjustment by Poisson Equation
Directory of Open Access Journals (Sweden)
Ana-Belen Petro
2013-09-01
Full Text Available Poisson Image Editing is a new technique permitting to modify the gradient vector field of an image, and then to recover an image with a gradient approaching this modified gradient field. This amounts to solve a Poisson equation, an operation which can be efficiently performed by Fast Fourier Transform (FFT. This paper describes an algorithm applying this technique, with two different variants. The first variant enhances the contrast by increasing the gradient in the dark regions of the image. This method is well adapted to images with back light or strong shadows, and reveals details in the shadows. The second variant of the same Poisson technique enhances all small gradients in the image, thus also sometimes revealing details and texture.
Poisson-Jacobi reduction of homogeneous tensors
International Nuclear Information System (INIS)
Grabowski, J; Iglesias, D; Marrero, J C; Padron, E; Urbanski, P
2004-01-01
The notion of homogeneous tensors is discussed. We show that there is a one-to-one correspondence between multivector fields on a manifold M, homogeneous with respect to a vector field Δ on M, and first-order polydifferential operators on a closed submanifold N of codimension 1 such that Δ is transversal to N. This correspondence relates the Schouten-Nijenhuis bracket of multivector fields on M to the Schouten-Jacobi bracket of first-order polydifferential operators on N and generalizes the Poissonization of Jacobi manifolds. Actually, it can be viewed as a super-Poissonization. This procedure of passing from a homogeneous multivector field to a first-order polydifferential operator can also be understood as a sort of reduction; in the standard case-a half of a Poisson reduction. A dual version of the above correspondence yields in particular the correspondence between Δ-homogeneous symplectic structures on M and contact structures on N
Poplová, Michaela; Sovka, Pavel; Cifra, Michal
2017-01-01
Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.
Exponential Stability of Stochastic Systems with Delay and Poisson Jumps
Directory of Open Access Journals (Sweden)
Wenli Zhu
2014-01-01
Full Text Available This paper focuses on the model of a class of nonlinear stochastic delay systems with Poisson jumps based on Lyapunov stability theory, stochastic analysis, and inequality technique. The existence and uniqueness of the adapted solution to such systems are proved by applying the fixed point theorem. By constructing a Lyapunov function and using Doob’s martingale inequality and Borel-Cantelli lemma, sufficient conditions are given to establish the exponential stability in the mean square of such systems, and we prove that the exponentially stable in the mean square of such systems implies the almost surely exponentially stable. The obtained results show that if stochastic systems is exponentially stable and the time delay is sufficiently small, then the corresponding stochastic delay systems with Poisson jumps will remain exponentially stable, and time delay upper limit is solved by using the obtained results when the system is exponentially stable, and they are more easily verified and applied in practice.
Improved mesh generator for the POISSON Group Codes
International Nuclear Information System (INIS)
Gupta, R.C.
1987-01-01
This paper describes the improved mesh generator of the POISSON Group Codes. These improvements enable one to have full control over the way the mesh is generated and in particular the way the mesh density is distributed throughout this model. A higher mesh density in certain regions coupled with a successively lower mesh density in others keeps the accuracy of the field computation high and the requirements on the computer time and computer memory low. The mesh is generated with the help of codes AUTOMESH and LATTICE; both have gone through a major upgrade. Modifications have also been made in the POISSON part of these codes. We shall present an example of a superconducting dipole magnet to explain how to use this code. The results of field computations are found to be reliable within a few parts in a hundred thousand even in such complex geometries
Equilibrium stochastic dynamics of Poisson cluster ensembles
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L.Bogachev
2008-06-01
Full Text Available The distribution μ of a Poisson cluster process in Χ=Rd (with n-point clusters is studied via the projection of an auxiliary Poisson measure in the space of configurations in Χn, with the intensity measure being the convolution of the background intensity (of cluster centres with the probability distribution of a generic cluster. We show that μ is quasi-invariant with respect to the group of compactly supported diffeomorphisms of Χ, and prove an integration by parts formula for μ. The corresponding equilibrium stochastic dynamics is then constructed using the method of Dirichlet forms.
White Noise of Poisson Random Measures
Proske, Frank; Øksendal, Bernt
2002-01-01
We develop a white noise theory for Poisson random measures associated with a Lévy process. The starting point of this theory is a chaos expansion with kernels of polynomial type. We use this to construct the white noise of a Poisson random measure, which takes values in a certain distribution space. Then we show, how a Skorohod/Itô integral for point processes can be represented by a Bochner integral in terms of white noise of the random measure and a Wick product. Further, we apply these co...
Bayesian regression of piecewise homogeneous Poisson processes
Directory of Open Access Journals (Sweden)
Diego Sevilla
2015-12-01
Full Text Available In this paper, a Bayesian method for piecewise regression is adapted to handle counting processes data distributed as Poisson. A numerical code in Mathematica is developed and tested analyzing simulated data. The resulting method is valuable for detecting breaking points in the count rate of time series for Poisson processes. Received: 2 November 2015, Accepted: 27 November 2015; Edited by: R. Dickman; Reviewed by: M. Hutter, Australian National University, Canberra, Australia.; DOI: http://dx.doi.org/10.4279/PIP.070018 Cite as: D J R Sevilla, Papers in Physics 7, 070018 (2015
Supersymmetric quantum corrections and Poisson-Lie T-duality
International Nuclear Information System (INIS)
Assaoui, F.; Lhallabi, T.; Abdus Salam International Centre for Theoretical Physics, Trieste
2000-07-01
The quantum actions of the (4,4) supersymmetric non-linear sigma model and its dual in the Abelian case are constructed by using the background superfield method. The propagators of the quantum superfield and its dual and the gauge fixing actions of the original and dual (4,4) supersymmetric sigma models are determined. On the other hand, the BRST transformations are used to obtain the quantum dual action of the (4,4) supersymmetric nonlinear sigma model in the sense of Poisson-Lie T-duality. (author)
Soft network materials with isotropic negative Poisson's ratios over large strains.
Liu, Jianxing; Zhang, Yihui
2018-01-31
Auxetic materials with negative Poisson's ratios have important applications across a broad range of engineering areas, such as biomedical devices, aerospace engineering and automotive engineering. A variety of design strategies have been developed to achieve artificial auxetic materials with controllable responses in the Poisson's ratio. The development of designs that can offer isotropic negative Poisson's ratios over large strains can open up new opportunities in emerging biomedical applications, which, however, remains a challenge. Here, we introduce deterministic routes to soft architected materials that can be tailored precisely to yield the values of Poisson's ratio in the range from -1 to 1, in an isotropic manner, with a tunable strain range from 0% to ∼90%. The designs rely on a network construction in a periodic lattice topology, which incorporates zigzag microstructures as building blocks to connect lattice nodes. Combined experimental and theoretical studies on broad classes of network topologies illustrate the wide-ranging utility of these concepts. Quantitative mechanics modeling under both infinitesimal and finite deformations allows the development of a rigorous design algorithm that determines the necessary network geometries to yield target Poisson ratios over desired strain ranges. Demonstrative examples in artificial skin with both the negative Poisson's ratio and the nonlinear stress-strain curve precisely matching those of the cat's skin and in unusual cylindrical structures with engineered Poisson effect and shape memory effect suggest potential applications of these network materials.
Spatial Nonhomogeneous Poisson Process in Corrosion Management
López De La Cruz, J.; Kuniewski, S.P.; Van Noortwijk, J.M.; Guriérrez, M.A.
2008-01-01
A method to test the assumption of nonhomogeneous Poisson point processes is implemented to analyze corrosion pit patterns. The method is calibrated with three artificially generated patterns and manages to accurately assess whether a pattern distribution is random, regular, or clustered. The
Efficient information transfer by Poisson neurons
Czech Academy of Sciences Publication Activity Database
Košťál, Lubomír; Shinomoto, S.
2016-01-01
Roč. 13, č. 3 (2016), s. 509-520 ISSN 1547-1063 R&D Projects: GA ČR(CZ) GA15-08066S Institutional support: RVO:67985823 Keywords : information capacity * Poisson neuron * metabolic cost * decoding error Subject RIV: BD - Theory of Information Impact factor: 1.035, year: 2016
Poisson brackets for fluids and plasmas
International Nuclear Information System (INIS)
Morrison, P.J.
1982-01-01
Noncanonical yet Hamiltonian descriptions are presented of many of the non-dissipative field equations that govern fluids and plasmas. The dynamical variables are the usually encountered physical variables. These descriptions have the advantage that gauge conditions are absent, but at the expense of introducing peculiar Poisson brackets. Clebsch-like potential descriptions that reverse this situations are also introduced
Almost Poisson integration of rigid body systems
International Nuclear Information System (INIS)
Austin, M.A.; Krishnaprasad, P.S.; Li-Sheng Wang
1993-01-01
In this paper we discuss the numerical integration of Lie-Poisson systems using the mid-point rule. Since such systems result from the reduction of hamiltonian systems with symmetry by lie group actions, we also present examples of reconstruction rules for the full dynamics. A primary motivation is to preserve in the integration process, various conserved quantities of the original dynamics. A main result of this paper is an O(h 3 ) error estimate for the Lie-Poisson structure, where h is the integration step-size. We note that Lie-Poisson systems appear naturally in many areas of physical science and engineering, including theoretical mechanics of fluids and plasmas, satellite dynamics, and polarization dynamics. In the present paper we consider a series of progressively complicated examples related to rigid body systems. We also consider a dissipative example associated to a Lie-Poisson system. The behavior of the mid-point rule and an associated reconstruction rule is numerically explored. 24 refs., 9 figs
Dimensional reduction for generalized Poisson brackets
Acatrinei, Ciprian Sorin
2008-02-01
We discuss dimensional reduction for Hamiltonian systems which possess nonconstant Poisson brackets between pairs of coordinates and between pairs of momenta. The associated Jacobi identities imply that the dimensionally reduced brackets are always constant. Some examples are given alongside the general theory.
Semiclassical limit and well-posedness of nonlinear Schrodinger-Poisson systems
Directory of Open Access Journals (Sweden)
Hailiang Li
2003-09-01
Full Text Available This paper concerns the well-posedness and semiclassical limit of nonlinear Schrodinger-Poisson systems. We show the local well-posedness and the existence of semiclassical limit of the two models for initial data with Sobolev regularity, before shocks appear in the limit system. We establish the existence of a global solution and show the time-asymptotic behavior of a classical solutions of Schrodinger-Poisson system for a fixed re-scaled Planck constant.
A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments
Energy Technology Data Exchange (ETDEWEB)
Fisicaro, G., E-mail: giuseppe.fisicaro@unibas.ch; Goedecker, S. [Department of Physics, University of Basel, Klingelbergstrasse 82, 4056 Basel (Switzerland); Genovese, L. [University of Grenoble Alpes, CEA, INAC-SP2M, L-Sim, F-38000 Grenoble (France); Andreussi, O. [Institute of Computational Science, Università della Svizzera Italiana, Via Giuseppe Buffi 13, CH-6904 Lugano (Switzerland); Theory and Simulations of Materials (THEOS) and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, Station 12, CH-1015 Lausanne (Switzerland); Marzari, N. [Theory and Simulations of Materials (THEOS) and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, Station 12, CH-1015 Lausanne (Switzerland)
2016-01-07
The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and the linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.
A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments
International Nuclear Information System (INIS)
Fisicaro, G.; Goedecker, S.; Genovese, L.; Andreussi, O.; Marzari, N.
2016-01-01
The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and the linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes
Seyoum, Awoke; Ndlovu, Principal; Zewotir, Temesgen
2016-01-01
CD4 cells are a type of white blood cells that plays a significant role in protecting humans from infectious diseases. Lack of information on associated factors on CD4 cell count reduction is an obstacle for improvement of cells in HIV positive adults. Therefore, the main objective of this study was to investigate baseline factors that could affect initial CD4 cell count change after highly active antiretroviral therapy had been given to adult patients in North West Ethiopia. A retrospective cross-sectional study was conducted among 792 HIV positive adult patients who already started antiretroviral therapy for 1 month of therapy. A Chi square test of association was used to assess of predictor covariates on the variable of interest. Data was secondary source and modeled using generalized linear models, especially Quasi-Poisson regression. The patients' CD4 cell count changed within a month ranged from 0 to 109 cells/mm 3 with a mean of 15.9 cells/mm 3 and standard deviation 18.44 cells/mm 3 . The first month CD4 cell count change was significantly affected by poor adherence to highly active antiretroviral therapy (aRR = 0.506, P value = 2e -16 ), fair adherence (aRR = 0.592, P value = 0.0120), initial CD4 cell count (aRR = 1.0212, P value = 1.54e -15 ), low household income (aRR = 0.63, P value = 0.671e -14 ), middle income (aRR = 0.74, P value = 0.629e -12 ), patients without cell phone (aRR = 0.67, P value = 0.615e -16 ), WHO stage 2 (aRR = 0.91, P value = 0.0078), WHO stage 3 (aRR = 0.91, P value = 0.0058), WHO stage 4 (0876, P value = 0.0214), age (aRR = 0.987, P value = 0.000) and weight (aRR = 1.0216, P value = 3.98e -14 ). Adherence to antiretroviral therapy, initial CD4 cell count, household income, WHO stages, age, weight and owner of cell phone played a major role for the variation of CD4 cell count in our data. Hence, we recommend a close follow-up of patients to adhere the prescribed medication for
Optimized thick-wall cylinders by virtue of Poisson's ratio selection
International Nuclear Information System (INIS)
Whitty, J.P.M.; Henderson, B.; Francis, J.; Lloyd, N.
2011-01-01
The principal stress distributions in thick-wall cylinders due to variation in the Poisson's ratio are predicted using analytical and finite element methods. Analyses of appropriate brittle and ductile failure criteria show that under the isochoric pressure conditions investigated that auextic (i.e. those possessing a negative Poisson's ratio) materials act as stress concentrators; hence they are predicted to fail before their conventional (i.e. possessing a positive Poisson's ratio) material counterparts. The key finding of the work presented shows that for constrained thick-wall cylinders the maximum tensile principal stress can vanish at a particular Poisson's ratio and aspect ratio. This phenomenon is exploited in order to present an optimized design criterion for thick-wall cylinders. Moreover, via the use of a cogent finite element model, this criterion is also shown to be applicable for the design of micro-porous materials.
Remarks on 'Poisson ratio beyond the limits of the elasticity theory'
International Nuclear Information System (INIS)
Wojciechowski, K.W.
2002-12-01
The non-chiral, elastically isotropic model exhibits Poison ratios in the range -1 ≤ σ ≤ 1 without any molecular rotation. The centres of discs-atoms are replaced in the vertices of a perfect triangle of the side length equal to σ. The positive sign of the Lame constant λ is not necessary for the stability of an isotropic system at any dimensionality. As the upper limit for the Poisson ratio in 2D isotropic systems is 1, crystalline or polycrystalline 2D systems can be obtained having the Poisson ratio exceeding 1/2. Both the traditional theory of elasticity and the Cosserat one exclude Poisson ratios exceeding 1/2 in 3D isotropic systems. Neighter anisotropy nor rotation are necessary to obtain extreme values of the Poisson ratio (author)
Linear odd Poisson bracket on Grassmann variables
International Nuclear Information System (INIS)
Soroka, V.A.
1999-01-01
A linear odd Poisson bracket (antibracket) realized solely in terms of Grassmann variables is suggested. It is revealed that the bracket, which corresponds to a semi-simple Lie group, has at once three Grassmann-odd nilpotent Δ-like differential operators of the first, the second and the third orders with respect to Grassmann derivatives, in contrast with the canonical odd Poisson bracket having the only Grassmann-odd nilpotent differential Δ-operator of the second order. It is shown that these Δ-like operators together with a Grassmann-odd nilpotent Casimir function of this bracket form a finite-dimensional Lie superalgebra. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)
Directory of Open Access Journals (Sweden)
Yan Wang
2014-08-01
Full Text Available CRBP1 (cellular retinol binding protein 1 and CRBP3 (cellular retinol binding protein 3, are important components of the retinoid signaling pathway and take part in vitamin A absorption, transport and metabolism. Based on the role of vitamin A in chicken laying performance, we investigated the polymorphism of CRBP1 and CRBP3 genes in 349 chickens using single strand conformation polymorphism and DNA sequencing methods. Only one polymorphism was identified in the third intron of CRBP1, two polymorphisms were detected in CRBP3; they were located in the second intron and the third intron respectively. The association studies between these three SNPs and laying performance traits were performed in Erlang mountainous chicken. Notably, the SNP g.14604G>T of CRBP1 was shown to be significantly associated with body weight at first egg (BWFE, age at first egg (AFE, weight at first egg (WFE and total number of eggs with 300 age (EN. The CRBP3 polymorphism g.934C>G was associated with AFE, and the g.1324A>G was associated with AFE and BWFE, but none of these polymorphisms were associated with egg quality traits. Haplotype combinations constructed on these two SNPs of CRBP3 gene were associated with BWFE and AFE. In particular, diplotype H2H2 had positive effect on AFE, BWFE, EN, and average egg-laying interval. We herein describe for the first time basic research on the polymorphism of chicken CRBP1 and CRBP3 genes that is predictive of genetic potential for laying performance in chicken.
Degenerate odd Poisson bracket on Grassmann variables
International Nuclear Information System (INIS)
Soroka, V.A.
2000-01-01
A linear degenerate odd Poisson bracket (antibracket) realized solely on Grassmann variables is proposed. It is revealed that this bracket has at once three Grassmann-odd nilpotent Δ-like differential operators of the first, second and third orders with respect to the Grassmann derivatives. It is shown that these Δ-like operators, together with the Grassmann-odd nilpotent Casimir function of this bracket, form a finite-dimensional Lie superalgebra
Poisson/Superfish codes for personal computers
International Nuclear Information System (INIS)
Humphries, S.
1992-01-01
The Poisson/Superfish codes calculate static E or B fields in two-dimensions and electromagnetic fields in resonant structures. New versions for 386/486 PCs and Macintosh computers have capabilities that exceed the mainframe versions. Notable improvements are interactive graphical post-processors, improved field calculation routines, and a new program for charged particle orbit tracking. (author). 4 refs., 1 tab., figs
Elementary derivation of Poisson structures for fluid dynamics and electrodynamics
International Nuclear Information System (INIS)
Kaufman, A.N.
1982-01-01
The canonical Poisson structure of the microscopic Lagrangian is used to deduce the noncanonical Poisson structure for the macroscopic Hamiltonian dynamics of a compressible neutral fluid and of fluid electrodynamics
Reduction of Nambu-Poisson Manifolds by Regular Distributions
Das, Apurba
2018-03-01
The version of Marsden-Ratiu reduction theorem for Nambu-Poisson manifolds by a regular distribution has been studied by Ibáñez et al. In this paper we show that the reduction is always ensured unless the distribution is zero. Next we extend the more general Falceto-Zambon Poisson reduction theorem for Nambu-Poisson manifolds. Finally, we define gauge transformations of Nambu-Poisson structures and show that these transformations commute with the reduction procedure.
Team behaviour analysis in sports using the poisson equation
Direkoglu, Cem; O'Connor, Noel E.
2012-01-01
We propose a novel physics-based model for analysing team play- ers’ positions and movements on a sports playing field. The goal is to detect for each frame the region with the highest population of a given team’s players and the region towards which the team is moving as they press for territorial advancement, termed the region of intent. Given the positions of team players from a plan view of the playing field at any given time, we solve a particular Poisson equation to generate a smooth di...
An approach to numerically solving the Poisson equation
Feng, Zhichen; Sheng, Zheng-Mao
2015-06-01
We introduce an approach for numerically solving the Poisson equation by using a physical model, which is a way to solve a partial differential equation without the finite difference method. This method is especially useful for obtaining the solutions in very many free-charge neutral systems with open boundary conditions. It can be used for arbitrary geometry and mesh style and is more efficient comparing with the widely-used iterative algorithm with multigrid methods. It is especially suitable for parallel computing. This method can also be applied to numerically solving other partial differential equations whose Green functions exist in analytic expression.
Large Time Behavior of the Vlasov-Poisson-Boltzmann System
Directory of Open Access Journals (Sweden)
Li Li
2013-01-01
Full Text Available The motion of dilute charged particles can be modeled by Vlasov-Poisson-Boltzmann system. We study the large time stability of the VPB system. To be precise, we prove that when time goes to infinity, the solution of VPB system tends to global Maxwellian state in a rate Ot−∞, by using a method developed for Boltzmann equation without force in the work of Desvillettes and Villani (2005. The improvement of the present paper is the removal of condition on parameter λ as in the work of Li (2008.
Improving EWMA Plans for Detecting Unusual Increases in Poisson Counts
Directory of Open Access Journals (Sweden)
R. S. Sparks
2009-01-01
adaptive exponentially weighted moving average (EWMA plan is developed for signalling unusually high incidence when monitoring a time series of nonhomogeneous daily disease counts. A Poisson transitional regression model is used to fit background/expected trend in counts and provides “one-day-ahead” forecasts of the next day's count. Departures of counts from their forecasts are monitored. The paper outlines an approach for improving early outbreak data signals by dynamically adjusting the exponential weights to be efficient at signalling local persistent high side changes. We emphasise outbreak signals in steady-state situations; that is, changes that occur after the EWMA statistic had run through several in-control counts.
Sparsity-based Poisson denoising with dictionary learning.
Giryes, Raja; Elad, Michael
2014-12-01
The problem of Poisson denoising appears in various imaging applications, such as low-light photography, medical imaging, and microscopy. In cases of high SNR, several transformations exist so as to convert the Poisson noise into an additive-independent identically distributed. Gaussian noise, for which many effective algorithms are available. However, in a low-SNR regime, these transformations are significantly less accurate, and a strategy that relies directly on the true noise statistics is required. Salmon et al took this route, proposing a patch-based exponential image representation model based on Gaussian mixture model, leading to state-of-the-art results. In this paper, we propose to harness sparse-representation modeling to the image patches, adopting the same exponential idea. Our scheme uses a greedy pursuit with boot-strapping-based stopping condition and dictionary learning within the denoising process. The reconstruction performance of the proposed scheme is competitive with leading methods in high SNR and achieving state-of-the-art results in cases of low SNR.
Algebraic properties of compatible Poisson brackets
Zhang, Pumei
2014-05-01
We discuss algebraic properties of a pencil generated by two compatible Poisson tensors A( x) and B( x). From the algebraic viewpoint this amounts to studying the properties of a pair of skew-symmetric bilinear forms A and B defined on a finite-dimensional vector space. We describe the Lie group G P of linear automorphisms of the pencil P = { A + λB}. In particular, we obtain an explicit formula for the dimension of G P and discuss some other algebraic properties such as solvability and Levi-Malcev decomposition.
Modified Poisson solver for the simulation of the silicon-oxide interface in semiconductor detectors
Energy Technology Data Exchange (ETDEWEB)
Castoldi, A. E-mail: andrea.castoldi@polimi.it; Rehak, P.; Gatti, E.; Guazzoni, C.; De Geronimo, G
2000-01-11
We present a modified Poisson solver for depleted semiconductor detectors that takes into account the effects of possible accumulation of mobile charge at the silicon-oxide interfaces. The solver is based on a physical model that closely approximates the correct boundary condition at the silicon-oxide interface. The model assumes that the silicon-oxide interface is divided into an equipotential region, where the electron layer is located, and a fully depleted region. The actual extension and potential of the electron layer region are approximated with the desired accuracy by an iterative procedure. This model has been implemented in 2- and 3-D Poisson solvers. The comparison with a 2-D drift-diffusion simulator has shown the accuracy of the proposed method. The modified Poisson solver has shown to be useful in giving accurate solutions to 3-D design problems at high CPU speed.
Modified Poisson solver for the simulation of the silicon-oxide interface in semiconductor detectors
Castoldi, A; Gatti, E; Guazzoni, C; De Geronimo, G
2000-01-01
We present a modified Poisson solver for depleted semiconductor detectors that takes into account the effects of possible accumulation of mobile charge at the silicon-oxide interfaces. The solver is based on a physical model that closely approximates the correct boundary condition at the silicon-oxide interface. The model assumes that the silicon-oxide interface is divided into an equipotential region, where the electron layer is located, and a fully depleted region. The actual extension and potential of the electron layer region are approximated with the desired accuracy by an iterative procedure. This model has been implemented in 2- and 3-D Poisson solvers. The comparison with a 2-D drift-diffusion simulator has shown the accuracy of the proposed method. The modified Poisson solver has shown to be useful in giving accurate solutions to 3-D design problems at high CPU speed.
Binomial vs poisson statistics in radiation studies
International Nuclear Information System (INIS)
Foster, J.; Kouris, K.; Spyrou, N.M.; Matthews, I.P.; Welsh National School of Medicine, Cardiff
1983-01-01
The processes of radioactive decay, decay and growth of radioactive species in a radioactive chain, prompt emission(s) from nuclear reactions, conventional activation and cyclic activation are discussed with respect to their underlying statistical density function. By considering the transformation(s) that each nucleus may undergo it is shown that all these processes are fundamentally binomial. Formally, when the number of experiments N is large and the probability of success p is close to zero, the binomial is closely approximated by the Poisson density function. In radiation and nuclear physics, N is always large: each experiment can be conceived of as the observation of the fate of each of the N nuclei initially present. Whether p, the probability that a given nucleus undergoes a prescribed transformation, is close to zero depends on the process and nuclide(s) concerned. Hence, although a binomial description is always valid, the Poisson approximation is not always adequate. Therefore further clarification is provided as to when the binomial distribution must be used in the statistical treatment of detected events. (orig.)
Modelling and Simulation of Asynchronous Real-Time Systems using Timed Rebeca
Directory of Open Access Journals (Sweden)
Luca Aceto
2011-07-01
Full Text Available In this paper we propose an extension of the Rebeca language that can be used to model distributed and asynchronous systems with timing constraints. We provide the formal semantics of the language using Structural Operational Semantics, and show its expressiveness by means of examples. We developed a tool for automated translation from timed Rebeca to the Erlang language, which provides a first implementation of timed Rebeca. We can use the tool to set the parameters of timed Rebeca models, which represent the environment and component variables, and use McErlang to run multiple simulations for different settings. Timed Rebeca restricts the modeller to a pure asynchronous actor-based paradigm, where the structure of the model represents the service oriented architecture, while the computational model matches the network infrastructure. Simulation is shown to be an effective analysis support, specially where model checking faces almost immediate state explosion in an asynchronous setting.
Random walk in dynamically disordered chains: Poisson white noise disorder
International Nuclear Information System (INIS)
Hernandez-Garcia, E.; Pesquera, L.; Rodriguez, M.A.; San Miguel, M.
1989-01-01
Exact solutions are given for a variety of models of random walks in a chain with time-dependent disorder. Dynamic disorder is modeled by white Poisson noise. Models with site-independent (global) and site-dependent (local) disorder are considered. Results are described in terms of an affective random walk in a nondisordered medium. In the cases of global disorder the effective random walk contains multistep transitions, so that the continuous limit is not a diffusion process. In the cases of local disorder the effective process is equivalent to usual random walk in the absence of disorder but with slower diffusion. Difficulties associated with the continuous-limit representation of random walk in a disordered chain are discussed. In particular, the authors consider explicit cases in which taking the continuous limit and averaging over disorder sources do not commute
Prescription-induced jump distributions in multiplicative Poisson processes
Suweis, Samir; Porporato, Amilcare; Rinaldo, Andrea; Maritan, Amos
2011-06-01
Generalized Langevin equations (GLE) with multiplicative white Poisson noise pose the usual prescription dilemma leading to different evolution equations (master equations) for the probability distribution. Contrary to the case of multiplicative Gaussian white noise, the Stratonovich prescription does not correspond to the well-known midpoint (or any other intermediate) prescription. By introducing an inertial term in the GLE, we show that the Itô and Stratonovich prescriptions naturally arise depending on two time scales, one induced by the inertial term and the other determined by the jump event. We also show that, when the multiplicative noise is linear in the random variable, one prescription can be made equivalent to the other by a suitable transformation in the jump probability distribution. We apply these results to a recently proposed stochastic model describing the dynamics of primary soil salinization, in which the salt mass balance within the soil root zone requires the analysis of different prescriptions arising from the resulting stochastic differential equation forced by multiplicative white Poisson noise, the features of which are tailored to the characters of the daily precipitation. A method is finally suggested to infer the most appropriate prescription from the data.
Hadayeghi, Alireza; Shalaby, Amer S; Persaud, Bhagwant N
2010-03-01
A common technique used for the calibration of collision prediction models is the Generalized Linear Modeling (GLM) procedure with the assumption of Negative Binomial or Poisson error distribution. In this technique, fixed coefficients that represent the average relationship between the dependent variable and each explanatory variable are estimated. However, the stationary relationship assumed may hide some important spatial factors of the number of collisions at a particular traffic analysis zone. Consequently, the accuracy of such models for explaining the relationship between the dependent variable and the explanatory variables may be suspected since collision frequency is likely influenced by many spatially defined factors such as land use, demographic characteristics, and traffic volume patterns. The primary objective of this study is to investigate the spatial variations in the relationship between the number of zonal collisions and potential transportation planning predictors, using the Geographically Weighted Poisson Regression modeling technique. The secondary objective is to build on knowledge comparing the accuracy of Geographically Weighted Poisson Regression models to that of Generalized Linear Models. The results show that the Geographically Weighted Poisson Regression models are useful for capturing spatially dependent relationships and generally perform better than the conventional Generalized Linear Models. Copyright 2009 Elsevier Ltd. All rights reserved.
A non-parametric estimator for the doubly-periodic Poisson intensity function
R. Helmers (Roelof); I.W. Mangku (Wayan); R. Zitikis
2007-01-01
textabstractIn a series of papers, J. Garrido and Y. Lu have proposed and investigated a doubly-periodic Poisson model, and then applied it to analyze hurricane data. The authors have suggested several parametric models for the underlying intensity function. In the present paper we construct and
Use of the negative binomial-truncated Poisson distribution in thunderstorm prediction
Cohen, A. C.
1971-01-01
A probability model is presented for the distribution of thunderstorms over a small area given that thunderstorm events (1 or more thunderstorms) are occurring over a larger area. The model incorporates the negative binomial and truncated Poisson distributions. Probability tables for Cape Kennedy for spring, summer, and fall months and seasons are presented. The computer program used to compute these probabilities is appended.
Poisson mixture distribution analysis for North Carolina SIDS counts using information criteria
Directory of Open Access Journals (Sweden)
Tyler Massaro
2017-09-01
Full Text Available Mixture distribution analysis provides us with a tool for identifying unlabeled clusters that naturally arise in a data set. In this paper, we demonstrate how to use the information criteria AIC and BIC to choose the optimal number of clusters for a given set of univariate Poisson data. We give an empirical comparison between minimum Hellinger distance (MHD estimation and EM estimation for finding parameters in a mixture of Poisson distributions with artificial data. In addition, we discuss Bayes error in the context of classification problems with mixture of 2, 3, 4, and 5 Poisson models. Finally, we provide an example with real data, taken from a study that looked at sudden infant death syndrome (SIDS count data from 100 North Carolina counties (Symons et al., 1983. This gives us an opportunity to demonstrate the advantages of the proposed model framework in comparison with the original analysis.
Stationary response of multi-degree-of-freedom vibro-impact systems to Poisson white noises
International Nuclear Information System (INIS)
Wu, Y.; Zhu, W.Q.
2008-01-01
The stationary response of multi-degree-of-freedom (MDOF) vibro-impact (VI) systems to random pulse trains is studied. The system is formulated as a stochastically excited and dissipated Hamiltonian system. The constraints are modeled as non-linear springs according to the Hertz contact law. The random pulse trains are modeled as Poisson white noises. The approximate stationary probability density function (PDF) for the response of MDOF dissipated Hamiltonian systems to Poisson white noises is obtained by solving the fourth-order generalized Fokker-Planck-Kolmogorov (FPK) equation using perturbation approach. As examples, two-degree-of-freedom (2DOF) VI systems under external and parametric Poisson white noise excitations, respectively, are investigated. The validity of the proposed approach is confirmed by using the results obtained from Monte Carlo simulation. It is shown that the non-Gaussian behaviour depends on the product of the mean arrival rate of the impulses and the relaxation time of the oscillator
On a Poisson homogeneous space of bilinear forms with a Poisson-Lie action
Chekhov, L. O.; Mazzocco, M.
2017-12-01
Let \\mathscr A be the space of bilinear forms on C^N with defining matrices A endowed with a quadratic Poisson structure of reflection equation type. The paper begins with a short description of previous studies of the structure, and then this structure is extended to systems of bilinear forms whose dynamics is governed by the natural action A\\mapsto B ABT} of the {GL}_N Poisson-Lie group on \\mathscr A. A classification is given of all possible quadratic brackets on (B, A)\\in {GL}_N× \\mathscr A preserving the Poisson property of the action, thus endowing \\mathscr A with the structure of a Poisson homogeneous space. Besides the product Poisson structure on {GL}_N× \\mathscr A, there are two other (mutually dual) structures, which (unlike the product Poisson structure) admit reductions by the Dirac procedure to a space of bilinear forms with block upper triangular defining matrices. Further generalisations of this construction are considered, to triples (B,C, A)\\in {GL}_N× {GL}_N× \\mathscr A with the Poisson action A\\mapsto B ACT}, and it is shown that \\mathscr A then acquires the structure of a Poisson symmetric space. Generalisations to chains of transformations and to the quantum and quantum affine algebras are investigated, as well as the relations between constructions of Poisson symmetric spaces and the Poisson groupoid. Bibliography: 30 titles.
On the Magnetic Shield for a Vlasov-Poisson Plasma
Caprino, Silvia; Cavallaro, Guido; Marchioro, Carlo
2017-12-01
We study the screening of a bounded body Γ against the effect of a wind of charged particles, by means of a shield produced by a magnetic field which becomes infinite on the border of Γ . The charged wind is modeled by a Vlasov-Poisson plasma, the bounded body by a torus, and the external magnetic field is taken close to the border of Γ . We study two models: a plasma composed by different species with positive or negative charges, and finite total mass of each species, and another made of many species of the same sign, each having infinite mass. We investigate the time evolution of both systems, showing in particular that the plasma particles cannot reach the body. Finally we discuss possible extensions to more general initial data. We show also that when the magnetic lines are straight lines, (that imposes an unbounded body), the previous results can be improved.
Periodic Poisson Solver for Particle Tracking
International Nuclear Information System (INIS)
Dohlus, M.; Henning, C.
2015-05-01
A method is described to solve the Poisson problem for a three dimensional source distribution that is periodic into one direction. Perpendicular to the direction of periodicity a free space (or open) boundary is realized. In beam physics, this approach allows to calculate the space charge field of a continualized charged particle distribution with periodic pattern. The method is based on a particle mesh approach with equidistant grid and fast convolution with a Green's function. The periodic approach uses only one period of the source distribution, but a periodic extension of the Green's function. The approach is numerically efficient and allows the investigation of periodic- and pseudo-periodic structures with period lengths that are small compared to the source dimensions, for instance of laser modulated beams or of the evolution of micro bunch structures. Applications for laser modulated beams are given.
Compound Poisson Approximations for Sums of Random Variables
Serfozo, Richard F.
1986-01-01
We show that a sum of dependent random variables is approximately compound Poisson when the variables are rarely nonzero and, given they are nonzero, their conditional distributions are nearly identical. We give several upper bounds on the total-variation distance between the distribution of such a sum and a compound Poisson distribution. Included is an example for Markovian occurrences of a rare event. Our bounds are consistent with those that are known for Poisson approximations for sums of...
Minimum Hellinger distance estimation for k-component poisson mixture with random effects.
Xiang, Liming; Yau, Kelvin K W; Van Hui, Yer; Lee, Andy H
2008-06-01
The k-component Poisson regression mixture with random effects is an effective model in describing the heterogeneity for clustered count data arising from several latent subpopulations. However, the residual maximum likelihood estimation (REML) of regression coefficients and variance component parameters tend to be unstable and may result in misleading inferences in the presence of outliers or extreme contamination. In the literature, the minimum Hellinger distance (MHD) estimation has been investigated to obtain robust estimation for finite Poisson mixtures. This article aims to develop a robust MHD estimation approach for k-component Poisson mixtures with normally distributed random effects. By applying the Gaussian quadrature technique to approximate the integrals involved in the marginal distribution, the marginal probability function of the k-component Poisson mixture with random effects can be approximated by the summation of a set of finite Poisson mixtures. Simulation study shows that the MHD estimates perform satisfactorily for data without outlying observation(s), and outperform the REML estimates when data are contaminated. Application to a data set of recurrent urinary tract infections (UTI) with random institution effects demonstrates the practical use of the robust MHD estimation method.
Poisson-Boltzmann versus Size-Modified Poisson-Boltzmann Electrostatics Applied to Lipid Bilayers.
Wang, Nuo; Zhou, Shenggao; Kekenes-Huskey, Peter M; Li, Bo; McCammon, J Andrew
2014-12-26
Mean-field methods, such as the Poisson-Boltzmann equation (PBE), are often used to calculate the electrostatic properties of molecular systems. In the past two decades, an enhancement of the PBE, the size-modified Poisson-Boltzmann equation (SMPBE), has been reported. Here, the PBE and the SMPBE are reevaluated for realistic molecular systems, namely, lipid bilayers, under eight different sets of input parameters. The SMPBE appears to reproduce the molecular dynamics simulation results better than the PBE only under specific parameter sets, but in general, it performs no better than the Stern layer correction of the PBE. These results emphasize the need for careful discussions of the accuracy of mean-field calculations on realistic systems with respect to the choice of parameters and call for reconsideration of the cost-efficiency and the significance of the current SMPBE formulation.
Basin, M.; Maldonado, J. J.; Zendejo, O.
2016-07-01
This paper proposes new mean-square filter and parameter estimator design for linear stochastic systems with unknown parameters over linear observations, where unknown parameters are considered as combinations of Gaussian and Poisson white noises. The problem is treated by reducing the original problem to a filtering problem for an extended state vector that includes parameters as additional states, modelled as combinations of independent Gaussian and Poisson processes. The solution to this filtering problem is based on the mean-square filtering equations for incompletely polynomial states confused with Gaussian and Poisson noises over linear observations. The resulting mean-square filter serves as an identifier for the unknown parameters. Finally, a simulation example shows effectiveness of the proposed mean-square filter and parameter estimator.
Measurements of the Poisson ratio and fragility of glass-forming liquids
DEFF Research Database (Denmark)
Christensen, Tage Emil; Olsen, Niels Boye
Recently much attention has been given to models and phenomenology of glass-forming liquids that correlates fast and slow degrees of freedom . In particular the Poisson ratio has been correlated with fragility. We present data on shear - and bulk modulus obtained by the techniques of the piezoele...... of the piezoelectric transducers PBG and PSG on a number of glass-forming liquids. Hereby the Poisson ratio can be found. Furthermore the PSG also gives the temperature dependence of shear viscosity and thereby the fragility. The validity of the conjectured relation is discussed...
A high order multi-resolution solver for the Poisson equation with application to vortex methods
DEFF Research Database (Denmark)
Hejlesen, Mads Mølholm; Spietz, Henrik Juul; Walther, Jens Honore
A high order method is presented for solving the Poisson equation subject to mixed free-space and periodic boundary conditions by using fast Fourier transforms (FFT). The high order convergence is achieved by deriving mollified Green’s functions from a high order regularization function which...... provides a correspondingly smooth solution to the Poisson equation.The high order regularization function may be obtained analogous to the approximate deconvolution method used in turbulence models and strongly relates to deblurring algorithms used in image processing. At first we show that the regularized...
Detecting overdispersion in count data: A zero-inflated Poisson regression analysis
Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Nor, Maria Elena; Mohamed, Maryati; Ismail, Norradihah
2017-09-01
This study focusing on analysing count data of butterflies communities in Jasin, Melaka. In analysing count dependent variable, the Poisson regression model has been known as a benchmark model for regression analysis. Continuing from the previous literature that used Poisson regression analysis, this study comprising the used of zero-inflated Poisson (ZIP) regression analysis to gain acute precision on analysing the count data of butterfly communities in Jasin, Melaka. On the other hands, Poisson regression should be abandoned in the favour of count data models, which are capable of taking into account the extra zeros explicitly. By far, one of the most popular models include ZIP regression model. The data of butterfly communities which had been called as the number of subjects in this study had been taken in Jasin, Melaka and consisted of 131 number of subjects visits Jasin, Melaka. Since the researchers are considering the number of subjects, this data set consists of five families of butterfly and represent the five variables involve in the analysis which are the types of subjects. Besides, the analysis of ZIP used the SAS procedure of overdispersion in analysing zeros value and the main purpose of continuing the previous study is to compare which models would be better than when exists zero values for the observation of the count data. The analysis used AIC, BIC and Voung test of 5% level significance in order to achieve the objectives. The finding indicates that there is a presence of over-dispersion in analysing zero value. The ZIP regression model is better than Poisson regression model when zero values exist.
Radio pulsar glitches as a state-dependent Poisson process
Fulgenzi, W.; Melatos, A.; Hughes, B. D.
2017-10-01
Gross-Pitaevskii simulations of vortex avalanches in a neutron star superfluid are limited computationally to ≲102 vortices and ≲102 avalanches, making it hard to study the long-term statistics of radio pulsar glitches in realistically sized systems. Here, an idealized, mean-field model of the observed Gross-Pitaevskii dynamics is presented, in which vortex unpinning is approximated as a state-dependent, compound Poisson process in a single random variable, the spatially averaged crust-superfluid lag. Both the lag-dependent Poisson rate and the conditional distribution of avalanche-driven lag decrements are inputs into the model, which is solved numerically (via Monte Carlo simulations) and analytically (via a master equation). The output statistics are controlled by two dimensionless free parameters: α, the glitch rate at a reference lag, multiplied by the critical lag for unpinning, divided by the spin-down rate; and β, the minimum fraction of the lag that can be restored by a glitch. The system evolves naturally to a self-regulated stationary state, whose properties are determined by α/αc(β), where αc(β) ≈ β-1/2 is a transition value. In the regime α ≳ αc(β), one recovers qualitatively the power-law size and exponential waiting-time distributions observed in many radio pulsars and Gross-Pitaevskii simulations. For α ≪ αc(β), the size and waiting-time distributions are both power-law-like, and a correlation emerges between size and waiting time until the next glitch, contrary to what is observed in most pulsars. Comparisons with astrophysical data are restricted by the small sample sizes available at present, with ≤35 events observed per pulsar.
The Analysis of Corporate Bond Valuation under an Infinite Dimensional Compound Poisson Framework
Directory of Open Access Journals (Sweden)
Sheng Fan
2014-01-01
Full Text Available This paper analyzes the firm bond valuation and credit spread with an endogenous model for the pure default and callable default corporate bond. Regarding the stochastic instantaneous forward rates and the firm value as an infinite dimensional Poisson process, we provide some analytical results for the embedded American options and firm bond valuations.
Poisson cohomology of scalar multidimensional Dubrovin-Novikov brackets
Carlet, Guido; Casati, Matteo; Shadrin, Sergey
2017-04-01
We compute the Poisson cohomology of a scalar Poisson bracket of Dubrovin-Novikov type with D independent variables. We find that the second and third cohomology groups are generically non-vanishing in D > 1. Hence, in contrast with the D = 1 case, the deformation theory in the multivariable case is non-trivial.
Avoiding negative populations in explicit Poisson tau-leaping.
Cao, Yang; Gillespie, Daniel T; Petzold, Linda R
2005-08-01
The explicit tau-leaping procedure attempts to speed up the stochastic simulation of a chemically reacting system by approximating the number of firings of each reaction channel during a chosen time increment tau as a Poisson random variable. Since the Poisson random variable can have arbitrarily large sample values, there is always the possibility that this procedure will cause one or more reaction channels to fire so many times during tau that the population of some reactant species will be driven negative. Two recent papers have shown how that unacceptable occurrence can be avoided by replacing the Poisson random variables with binomial random variables, whose values are naturally bounded. This paper describes a modified Poisson tau-leaping procedure that also avoids negative populations, but is easier to implement than the binomial procedure. The new Poisson procedure also introduces a second control parameter, whose value essentially dials the procedure from the original Poisson tau-leaping at one extreme to the exact stochastic simulation algorithm at the other; therefore, the modified Poisson procedure will generally be more accurate than the original Poisson procedure.
Formulation of Hamiltonian mechanics with even and odd Poisson brackets
International Nuclear Information System (INIS)
Khudaverdyan, O.M.; Nersesyan, A.P.
1987-01-01
A possibility is studied as to constrict the odd Poisson bracket and odd Hamiltonian by the given dynamics in phase superspace - the even Poisson bracket and even Hamiltonian so the transition to the new structure does not change the equations of motion. 9 refs
Cluster X-varieties, amalgamation, and Poisson-Lie groups
DEFF Research Database (Denmark)
Fock, V. V.; Goncharov, A. B.
2006-01-01
In this paper, starting from a split semisimple real Lie group G with trivial center, we define a family of varieties with additional structures. We describe them as cluster χ-varieties, as defined in [FG2]. In particular they are Poisson varieties. We define canonical Poisson maps of these varie...
Derivation of relativistic wave equation from the Poisson process
Indian Academy of Sciences (India)
Abstract. A Poisson process is one of the fundamental descriptions for relativistic particles: both fermions and bosons. A generalized linear photon wave equation in dispersive and homogeneous medium with dissipation is derived using the formulation of the Poisson process. This formulation provides a possible ...
Unimodularity criteria for Poisson structures on foliated manifolds
Pedroza, Andrés; Velasco-Barreras, Eduardo; Vorobiev, Yury
2018-03-01
We study the behavior of the modular class of an orientable Poisson manifold and formulate some unimodularity criteria in the semilocal context, around a (singular) symplectic leaf. Our results generalize some known unimodularity criteria for regular Poisson manifolds related to the notion of the Reeb class. In particular, we show that the unimodularity of the transverse Poisson structure of the leaf is a necessary condition for the semilocal unimodular property. Our main tool is an explicit formula for a bigraded decomposition of modular vector fields of a coupling Poisson structure on a foliated manifold. Moreover, we also exploit the notion of the modular class of a Poisson foliation and its relationship with the Reeb class.
Czech Academy of Sciences Publication Activity Database
Feireisl, Eduard; Laurençot, P.
2007-01-01
Roč. 88, - (2007), s. 325-349 ISSN 0021-7824 R&D Projects: GA ČR GA201/05/0164 Institutional research plan: CEZ:AV0Z10190503 Keywords : Navier-Stokes-Fourier- Poisson system * Smoluchowski- Poisson system * singular limit Subject RIV: BA - General Mathematics Impact factor: 1.118, year: 2007
Dynamics of a prey-predator system under Poisson white noise excitation
Pan, Shan-Shan; Zhu, Wei-Qiu
2014-10-01
The classical Lotka-Volterra (LV) model is a well-known mathematical model for prey-predator ecosystems. In the present paper, the pulse-type version of stochastic LV model, in which the effect of a random natural environment has been modeled as Poisson white noise, is investigated by using the stochastic averaging method. The averaged generalized Itô stochastic differential equation and Fokker-Planck-Kolmogorov (FPK) equation are derived for prey-predator ecosystem driven by Poisson white noise. Approximate stationary solution for the averaged generalized FPK equation is obtained by using the perturbation method. The effect of prey self-competition parameter ɛ2 s on ecosystem behavior is evaluated. The analytical result is confirmed by corresponding Monte Carlo (MC) simulation.
Eckalbar, John C; Eckalbar, Walter L
2015-03-01
This paper investigates the dynamics of an SIR model of childhood vaccination under the assumption that the vaccination uptake rate depends on past values of disease prevalence. The delay kernel is a high order Erlang function, which allows no instantaneous feedback between prevalence at time t and vaccinations at time t. Multiple types of endemic equilibria are found, as are stable and unstable equilibria, periodic orbits, dependence on initial conditions, and apparent chaos. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
A high order solver for the unbounded Poisson equation
DEFF Research Database (Denmark)
Hejlesen, Mads Mølholm; Rasmussen, Johannes Tophøj; Chatelain, Philippe
2013-01-01
A high order converging Poisson solver is presented, based on the Greenʼs function solution to Poissonʼs equation subject to free-space boundary conditions. The high order convergence is achieved by formulating regularised integration kernels, analogous to a smoothing of the solution field....... The method is extended to directly solve the derivatives of the solution to Poissonʼs equation. In this way differential operators such as the divergence or curl of the solution field can be solved to the same high order convergence without additional computational effort. The method, is applied...... and validated, however not restricted, to the equations of fluid mechanics, and can be used in many applications to solve Poissonʼs equation on a rectangular unbounded domain....
Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan
2011-11-01
To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.
Organisation spatiale du peuplement de poissons dans le Bandama ...
African Journals Online (AJOL)
L'évolution des peuplements de poissons sur le Bandama a été étudiée en considérant quatre zones d'échantillonnage : en amont du lac de Kossou, dans les lacs de Kossou et de Taabo, entre les lacs de Kossou et de Taabo, et en aval du lac de Taabo. Au total, 74 espèces de poisson réparties en 49 genres, 28 familles ...
Formality theory from Poisson structures to deformation quantization
Esposito, Chiara
2015-01-01
This book is a survey of the theory of formal deformation quantization of Poisson manifolds, in the formalism developed by Kontsevich. It is intended as an educational introduction for mathematical physicists who are dealing with the subject for the first time. The main topics covered are the theory of Poisson manifolds, star products and their classification, deformations of associative algebras and the formality theorem. Readers will also be familiarized with the relevant physical motivations underlying the purely mathematical construction.
On the Fedosov deformation quantization beyond the regular Poisson manifolds
International Nuclear Information System (INIS)
Dolgushev, V.A.; Isaev, A.P.; Lyakhovich, S.L.; Sharapov, A.A.
2002-01-01
A simple iterative procedure is suggested for the deformation quantization of (irregular) Poisson brackets associated to the classical Yang-Baxter equation. The construction is shown to admit a pure algebraic reformulation giving the Universal Deformation Formula (UDF) for any triangular Lie bialgebra. A simple proof of classification theorem for inequivalent UDF's is given. As an example the explicit quantization formula is presented for the quasi-homogeneous Poisson brackets on two-plane
A Note On the Estimation of the Poisson Parameter
Directory of Open Access Journals (Sweden)
S. S. Chitgopekar
1985-01-01
distribution when there are errors in observing the zeros and ones and obtains both the maximum likelihood and moments estimates of the Poisson mean and the error probabilities. It is interesting to note that either method fails to give unique estimates of these parameters unless the error probabilities are functionally related. However, it is equally interesting to observe that the estimate of the Poisson mean does not depend on the functional relationship between the error probabilities.
Downlink Non-Orthogonal Multiple Access (NOMA) in Poisson Networks
Ali, Konpal S.
2018-03-21
A network model is considered where Poisson distributed base stations transmit to $N$ power-domain non-orthogonal multiple access (NOMA) users (UEs) each that employ successive interference cancellation (SIC) for decoding. We propose three models for the clustering of NOMA UEs and consider two different ordering techniques for the NOMA UEs: mean signal power-based and instantaneous signal-to-intercell-interference-and-noise-ratio-based. For each technique, we present a signal-to-interference-and-noise ratio analysis for the coverage of the typical UE. We plot the rate region for the two-user case and show that neither ordering technique is consistently superior to the other. We propose two efficient algorithms for finding a feasible resource allocation that maximize the cell sum rate $\\\\mathcal{R}_{\\ m tot}$, for general $N$, constrained to: 1) a minimum rate $\\\\mathcal{T}$ for each UE, 2) identical rates for all UEs. We show the existence of: 1) an optimum $N$ that maximizes the constrained $\\\\mathcal{R}_{\\ m tot}$ given a set of network parameters, 2) a critical SIC level necessary for NOMA to outperform orthogonal multiple access. The results highlight the importance in choosing the network parameters $N$, the constraints, and the ordering technique to balance the $\\\\mathcal{R}_{\\ m tot}$ and fairness requirements. We also show that interference-aware UE clustering can significantly improve performance.
Lim, Jongil; Whitcomb, John; Boyd, James; Varghese, Julian
2007-01-01
A finite element implementation of the transient nonlinear Nernst-Planck-Poisson (NPP) and Nernst-Planck-Poisson-modified Stern (NPPMS) models is presented. The NPPMS model uses multipoint constraints to account for finite ion size, resulting in realistic ion concentrations even at high surface potential. The Poisson-Boltzmann equation is used to provide a limited check of the transient models for low surface potential and dilute bulk solutions. The effects of the surface potential and bulk molarity on the electric potential and ion concentrations as functions of space and time are studied. The ability of the models to predict realistic energy storage capacity is investigated. The predicted energy is much more sensitive to surface potential than to bulk solution molarity.
Ngai, K. L.; Wang, Li-Min; Liu, Riping; Wang, W. H.
2014-01-01
In metallic glasses a clear correlation had been established between plasticity or ductility with the Poisson's ratio νPoisson and alternatively the ratio of the elastic bulk modulus to the shear modulus, K/G. Such a correlation between these two macroscopic mechanical properties is intriguing and is challenging to explain from the dynamics on a microscopic level. A recent experimental study has found a connection of ductility to the secondary β-relaxation in metallic glasses. The strain rate and temperature dependencies of the ductile-brittle transition are similar to the reciprocal of the secondary β-relaxation time, τβ. Moreover, metallic glass is more ductile if the relaxation strength of the β-relaxation is larger and τβ is shorter. The findings indicate the β-relaxation is related to and instrumental for ductility. On the other hand, K/G or νPoisson is related to the effective Debye-Waller factor (i.e., the non-ergodicity parameter), f0, characterizing the dynamics of a structural unit inside a cage formed by other units, and manifested as the nearly constant loss shown in the frequency dependent susceptibility. We make the connection of f0 to the non-exponentiality parameter n in the Kohlrausch stretched exponential correlation function of the structural α-relaxation function, φ (t) = exp [ { - ( {t/{τ _α }})^{1 - n} }]. This connection follows from the fact that both f0 and n are determined by the inter-particle potential, and 1/f0 or (1 - f0) and n both increase with anharmonicity of the potential. A well tested result from the Coupling Model is used to show that τβ is completely determined by τα and n. From the string of relations, (i) K/G or νPoisson with 1/f0 or (1 - f0), (ii) 1/f0 or (1 - f0) with n, and (iii) τα and n with τβ, we arrive at the desired relation between K/G or νPoisson and τβ. On combining this relation with that between ductility and τβ, we have finally an explanation of the empirical correlation between
Cooperative HARQ with Poisson Interference and Opportunistic Routing
Kaveh, Mostafa
2014-01-06
This presentation considers reliable transmission of data from a source to a destination, aided cooperatively by wireless relays selected opportunistically and utilizing hybrid forward error correction/detection, and automatic repeat request (Hybrid ARQ, or HARQ). Specifically, we present a performance analysis of the cooperative HARQ protocol in a wireless adhoc multihop network employing spatial ALOHA. We model the nodes in such a network by a homogeneous 2-D Poisson point process. We study the tradeoff between the per-hop rate, spatial density and range of transmissions inherent in the network by optimizing the transport capacity with respect to the network design parameters, HARQ coding rate and medium access probability. We obtain an approximate analytic expression for the expected progress of opportunistic routing and optimize the capacity approximation by convex optimization. By way of numerical results, we show that the network design parameters obtained by optimizing the analytic approximation of transport capacity closely follows that of Monte Carlo based exact transport capacity optimization. As a result of the analysis, we argue that the optimal HARQ coding rate and medium access probability are independent of the node density in the network.
Poisson process approximation for sequence repeats, and sequencing by hybridization.
Arratia, R; Martin, D; Reinert, G; Waterman, M S
1996-01-01
Sequencing by hybridization is a tool to determine a DNA sequence from the unordered list of all l-tuples contained in this sequence; typical numbers for l are l = 8, 10, 12. For theoretical purposes we assume that the multiset of all l-tuples is known. This multiset determines the DNA sequence uniquely if none of the so-called Ukkonen transformations are possible. These transformations require repeats of (l-1)-tuples in the sequence, with these repeats occurring in certain spatial patterns. We model DNA as an i.i.d. sequence. We first prove Poisson process approximations for the process of indicators of all leftmost long repeats allowing self-overlap and for the process of indicators of all left-most long repeats without self-overlap. Using the Chen-Stein method, we get bounds on the error of these approximations. As a corollary, we approximate the distribution of longest repeats. In the second step we analyze the spatial patterns of the repeats. Finally we combine these two steps to prove an approximation for the probability that a random sequence is uniquely recoverable from its list of l-tuples. For all our results we give some numerical examples including error bounds.
Beyond standard Poisson-Boltzmann theory: ion-specific interactions in aqueous solutions
International Nuclear Information System (INIS)
Ben-Yaakov, Dan; Andelman, David; Harries, Daniel; Podgornik, Rudi
2009-01-01
The Poisson-Boltzmann mean-field description of ionic solutions has been successfully used in predicting charge distributions and interactions between charged macromolecules. While the electrostatic model of charged fluids, on which the Poisson-Boltzmann description rests, and its statistical mechanical consequences have been scrutinized in great detail, much less is understood about its probable shortcomings when dealing with various aspects of real physical, chemical and biological systems. These shortcomings are not only a consequence of the limitations of the mean-field approximation per se, but perhaps are primarily due to the fact that the purely Coulombic model Hamiltonian does not take into account various additional interactions that are not electrostatic in their origin. We explore several possible non-electrostatic contributions to the free energy of ions in confined aqueous solutions and investigate their ramifications and consequences on ionic profiles and interactions between charged surfaces and macromolecules.
Directory of Open Access Journals (Sweden)
García-Artiles, María Dolores
2014-12-01
Full Text Available This paper presents the zero-inflated generalised Poisson distribution, which is useful when there is a large presence of zeros in the sample. After presenting the model, we develop a specific program based on Mathematica, overcoming some limitations of alternative approaches such as STATA or EViews, which do not include the zero-inflated Poisson distribution among its routines. The advantages of the model used and the proposed program are illustrated with a real example that is very appropriate to its features, namely an analysis of the factors influencing university students’ attendance at tutoring sessions. This example is particularly suitable to show the usefulness of the methodology presented because it includes a large number of zeros, reflecting the many occasions on which the students do not attend these sessions. The students’ place of residence, their attendance at lectures and the application of continual assessment are variables that seem to account for attendance at tutoring sessions.
A spectral Poisson solver for kinetic plasma simulation
Szeremley, Daniel; Obberath, Jens; Brinkmann, Ralf
2011-10-01
Plasma resonance spectroscopy is a well established plasma diagnostic method, realized in several designs. One of these designs is the multipole resonance probe (MRP). In its idealized - geometrically simplified - version it consists of two dielectrically shielded, hemispherical electrodes to which an RF signal is applied. A numerical tool is under development which is capable of simulating the dynamics of the plasma surrounding the MRP in electrostatic approximation. In this contribution we concentrate on the specialized Poisson solver for that tool. The plasma is represented by an ensemble of point charges. By expanding both the charge density and the potential into spherical harmonics, a largely analytical solution of the Poisson problem can be employed. For a practical implementation, the expansion must be appropriately truncated. With this spectral solver we are able to efficiently solve the Poisson equation in a kinetic plasma simulation without the need of introducing a spatial discretization.
A high order solver for the unbounded Poisson equation
DEFF Research Database (Denmark)
Hejlesen, Mads Mølholm; Rasmussen, Johannes Tophøj; Chatelain, Philippe
In mesh-free particle methods a high order solution to the unbounded Poisson equation is usually achieved by constructing regularised integration kernels for the Biot-Savart law. Here the singular, point particles are regularised using smoothed particles to obtain an accurate solution with an order...... of convergence consistent with the moments conserved by the applied smoothing function. In the hybrid particle-mesh method of Hockney and Eastwood (HE) the particles are interpolated onto a regular mesh where the unbounded Poisson equation is solved by a discrete non-cyclic convolution of the mesh values...... and the integration kernel. In this work we show an implementation of high order regularised integration kernels in the HE algorithm for the unbounded Poisson equation to formally achieve an arbitrary high order convergence. We further present a quantitative study of the convergence rate to give further insight...
Effect of Poisson noise on adiabatic quantum control
Kiely, A.; Muga, J. G.; Ruschhaupt, A.
2017-01-01
We present a detailed derivation of the master equation describing a general time-dependent quantum system with classical Poisson white noise and outline its various properties. We discuss the limiting cases of Poisson white noise and provide approximations for the different noise strength regimes. We show that using the eigenstates of the noise superoperator as a basis can be a useful way of expressing the master equation. Using this, we simulate various settings to illustrate different effects of Poisson noise. In particular, we show a dip in the fidelity as a function of noise strength where high fidelity can occur in the strong-noise regime for some cases. We also investigate recent claims [J. Jing et al., Phys. Rev. A 89, 032110 (2014), 10.1103/PhysRevA.89.032110] that this type of noise may improve rather than destroy adiabaticity.
A finite element Poisson solver for gyrokinetic particle simulations in a global field aligned mesh
International Nuclear Information System (INIS)
Nishimura, Y.; Lin, Z.; Lewandowski, J.L.V.; Ethier, S.
2006-01-01
A new finite element Poisson solver is developed and applied to a global gyrokinetic toroidal code (GTC) which employs the field aligned mesh and thus a logically non-rectangular grid in a general geometry. Employing test cases where the analytical solutions are known, the finite element solver has been verified. The CPU time scaling versus the matrix size employing portable, extensible toolkit for scientific computation (PETSc) to solve the sparse matrix is promising. Taking the ion temperature gradient modes (ITG) as an example, the solution from the new finite element solver has been compared to the solution from the original GTC's iterative solver which is only efficient for adiabatic electrons. Linear and nonlinear simulation results from the two different forms of the gyrokinetic Poisson equation (integral form and the differential form) coincide each other. The new finite element solver enables the implementation of advanced kinetic electron models for global electromagnetic simulations
Poisson and negative binomial item count techniques for surveys with sensitive question.
Tian, Guo-Liang; Tang, Man-Lai; Wu, Qin; Liu, Yin
2017-04-01
Although the item count technique is useful in surveys with sensitive questions, privacy of those respondents who possess the sensitive characteristic of interest may not be well protected due to a defect in its original design. In this article, we propose two new survey designs (namely the Poisson item count technique and negative binomial item count technique) which replace several independent Bernoulli random variables required by the original item count technique with a single Poisson or negative binomial random variable, respectively. The proposed models not only provide closed form variance estimate and confidence interval within [0, 1] for the sensitive proportion, but also simplify the survey design of the original item count technique. Most importantly, the new designs do not leak respondents' privacy. Empirical results show that the proposed techniques perform satisfactorily in the sense that it yields accurate parameter estimate and confidence interval.
Vasta, M.; Di Paola, M.
In this paper an approximate explicit probability density function for the analysis of external oscillations of a linear and geometric nonlinear simply supported beam driven by random pulses is proposed. The adopted impulsive loading model is the Poisson White Noise , that is a process having Dirac's delta occurrences with random intensity distributed in time according to Poisson's law. The response probability density function can be obtained solving the related Kolmogorov-Feller (KF) integro-differential equation. An approximated solution, using path integral method, is derived transforming the KF equation to a first order partial differential equation. The method of characteristic is then applied to obtain an explicit solution. Different levels of approximation, depending on the physical assumption on the transition probability density function, are found and the solution for the response density is obtained as series expansion using convolution integrals.
Efficient Levenberg-Marquardt minimization of the maximum likelihood estimator for Poisson deviates
Energy Technology Data Exchange (ETDEWEB)
Laurence, T; Chromy, B
2009-11-10
Histograms of counted events are Poisson distributed, but are typically fitted without justification using nonlinear least squares fitting. The more appropriate maximum likelihood estimator (MLE) for Poisson distributed data is seldom used. We extend the use of the Levenberg-Marquardt algorithm commonly used for nonlinear least squares minimization for use with the MLE for Poisson distributed data. In so doing, we remove any excuse for not using this more appropriate MLE. We demonstrate the use of the algorithm and the superior performance of the MLE using simulations and experiments in the context of fluorescence lifetime imaging. Scientists commonly form histograms of counted events from their data, and extract parameters by fitting to a specified model. Assuming that the probability of occurrence for each bin is small, event counts in the histogram bins will be distributed according to the Poisson distribution. We develop here an efficient algorithm for fitting event counting histograms using the maximum likelihood estimator (MLE) for Poisson distributed data, rather than the non-linear least squares measure. This algorithm is a simple extension of the common Levenberg-Marquardt (L-M) algorithm, is simple to implement, quick and robust. Fitting using a least squares measure is most common, but it is the maximum likelihood estimator only for Gaussian-distributed data. Non-linear least squares methods may be applied to event counting histograms in cases where the number of events is very large, so that the Poisson distribution is well approximated by a Gaussian. However, it is not easy to satisfy this criterion in practice - which requires a large number of events. It has been well-known for years that least squares procedures lead to biased results when applied to Poisson-distributed data; a recent paper providing extensive characterization of these biases in exponential fitting is given. The more appropriate measure based on the maximum likelihood estimator (MLE
Quadratic Hamiltonians on non-symmetric Poisson structures
International Nuclear Information System (INIS)
Arribas, M.; Blesa, F.; Elipe, A.
2007-01-01
Many dynamical systems may be represented in a set of non-canonical coordinates that generate an su(2) algebraic structure. The topology of the phase space is the one of the S 2 sphere, the Poisson structure is the one of the rigid body, and the Hamiltonian is a parametric quadratic form in these 'spherical' coordinates. However, there are other problems in which the Poisson structure losses its symmetry. In this paper we analyze this case and, we show how the loss of the spherical symmetry affects the phase flow and parametric bifurcations for the bi-parametric cases
Efficient triangulation of Poisson-disk sampled point sets
Guo, Jianwei
2014-05-06
In this paper, we present a simple yet efficient algorithm for triangulating a 2D input domain containing a Poisson-disk sampled point set. The proposed algorithm combines a regular grid and a discrete clustering approach to speedup the triangulation. Moreover, our triangulation algorithm is flexible and performs well on more general point sets such as adaptive, non-maximal Poisson-disk sets. The experimental results demonstrate that our algorithm is robust for a wide range of input domains and achieves significant performance improvement compared to the current state-of-the-art approaches. © 2014 Springer-Verlag Berlin Heidelberg.
Gyrokinetic energy conservation and Poisson-bracket formulation
International Nuclear Information System (INIS)
Brizard, A.
1988-11-01
An integral expression for the gyrokinetic total energy of a magnetized plasma with general magnetic field configuration perturbed by fully electromagnetic fields was recently derived through the use of a gyro-center Lie transformation. We show that the gyrokinetic energy is conserved by the gyrokinetic Hamiltonian flow to all orders in perturbed fields. This paper is concerned with the explicit demonstration that a gyrokinetic Hamiltonian containing quadratic nonlinearities preserves the gyrokinetic energy up to third order. The Poisson-bracket formulation greatly facilitates this demonstration with the help of the Jacobi identity and other properties of the Poisson brackets. 18 refs
Adaptive maximal poisson-disk sampling on surfaces
Yan, Dongming
2012-01-01
In this paper, we study the generation of maximal Poisson-disk sets with varying radii on surfaces. Based on the concepts of power diagram and regular triangulation, we present a geometric analysis of gaps in such disk sets on surfaces, which is the key ingredient of the adaptive maximal Poisson-disk sampling framework. Moreover, we adapt the presented sampling framework for remeshing applications. Several novel and efficient operators are developed for improving the sampling/meshing quality over the state-of-theart. © 2012 ACM.
Robust iterative observer for source localization for Poisson equation
Majeed, Muhammad Usman
2017-01-05
Source localization problem for Poisson equation with available noisy boundary data is well known to be highly sensitive to noise. The problem is ill posed and lacks to fulfill Hadamards stability criteria for well posedness. In this work, first a robust iterative observer is presented for boundary estimation problem for Laplace equation, and then this algorithm along with the available noisy boundary data from the Poisson problem is used to localize point sources inside a rectangular domain. The algorithm is inspired from Kalman filter design, however one of the space variables is used as time-like. Numerical implementation along with simulation results is detailed towards the end.
Efficient maximal Poisson-disk sampling and remeshing on surfaces
Guo, Jianwei
2015-02-01
Poisson-disk sampling is one of the fundamental research problems in computer graphics that has many applications. In this paper, we study the problem of maximal Poisson-disk sampling on mesh surfaces. We present a simple approach that generalizes the 2D maximal sampling framework to surfaces. The key observation is to use a subdivided mesh as the sampling domain for conflict checking and void detection. Our approach improves the state-of-the-art approach in efficiency, quality and the memory consumption.
Stochastic Dynamics of a Time-Delayed Ecosystem Driven by Poisson White Noise Excitation
Directory of Open Access Journals (Sweden)
Wantao Jia
2018-02-01
Full Text Available We investigate the stochastic dynamics of a prey-predator type ecosystem with time delay and the discrete random environmental fluctuations. In this model, the delay effect is represented by a time delay parameter and the effect of the environmental randomness is modeled as Poisson white noise. The stochastic averaging method and the perturbation method are applied to calculate the approximate stationary probability density functions for both predator and prey populations. The influences of system parameters and the Poisson white noises are investigated in detail based on the approximate stationary probability density functions. It is found that, increasing time delay parameter as well as the mean arrival rate and the variance of the amplitude of the Poisson white noise will enhance the fluctuations of the prey and predator population. While the larger value of self-competition parameter will reduce the fluctuation of the system. Furthermore, the results from Monte Carlo simulation are also obtained to show the effectiveness of the results from averaging method.
Screened Poisson Equation for Image Contrast Enhancement
Directory of Open Access Journals (Sweden)
Jean-Michel Morel
2014-03-01
Full Text Available In this work we propose a discussion and detailed implementation of a very simple gradient domain method that tries to eliminate the effect of nonuniform illumination and at the same time preserves the images details. This model, which to the best of our knowledge has not been explored in spite of its simplicity, acts as a high pass filter. We show that with a single contrast parameter (which keeps the same value in most experiments, the model delivers state of the art results. They compare favorably to results obtained with more complex algorithms. Our algorithm is designed for all kinds of images, but with the special specification of making minimal image detail alteration thanks to a first order fidelity term, instead of the usual zero order term. Experiments on non-uniform medical images and on hazy images illustrate significant perception gain.
A convergent 2D finite-difference scheme for the Dirac-Poisson system and the simulation of graphene
Brinkman, Daniel
2014-01-01
We present a convergent finite-difference scheme of second order in both space and time for the 2D electromagnetic Dirac equation. We apply this method in the self-consistent Dirac-Poisson system to the simulation of graphene. The model is justified for low energies, where the particles have wave vectors sufficiently close to the Dirac points. In particular, we demonstrate that our method can be used to calculate solutions of the Dirac-Poisson system where potentials act as beam splitters or Veselago lenses. © 2013 Elsevier Inc.
On covariant Poisson brackets in classical field theory
International Nuclear Information System (INIS)
Forger, Michael; Salles, Mário O.
2015-01-01
How to give a natural geometric definition of a covariant Poisson bracket in classical field theory has for a long time been an open problem—as testified by the extensive literature on “multisymplectic Poisson brackets,” together with the fact that all these proposals suffer from serious defects. On the other hand, the functional approach does provide a good candidate which has come to be known as the Peierls–De Witt bracket and whose construction in a geometrical setting is now well understood. Here, we show how the basic “multisymplectic Poisson bracket” already proposed in the 1970s can be derived from the Peierls–De Witt bracket, applied to a special class of functionals. This relation allows to trace back most (if not all) of the problems encountered in the past to ambiguities (the relation between differential forms on multiphase space and the functionals they define is not one-to-one) and also to the fact that this class of functionals does not form a Poisson subalgebra
Poisson processes on groups and Feynman path integrals
International Nuclear Information System (INIS)
Combe, P.; Rodriguez, R.; Sirugue-Collin, M.; Centre National de la Recherche Scientifique, 13 - Marseille; Sirugue, M.
1979-09-01
An expression is given for the perturbed evolution of a free evolution by gentle, possibly velocity dependent, potential, in terms of the expectation with respect to a Poisson process on a group. Various applications are given in particular to usual quantum mechanics but also to Fermi and spin systems
The Quantum Poisson Bracket and Transformation Theory in ...
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 8; Issue 8. The Quantum Poisson Bracket and Transformation Theory in Quantum Mechanics: Dirac's Early Work in Quantum Theory. Kamal Datta. General Article Volume 8 Issue 8 August 2003 pp 75-85 ...
A high order solver for the unbounded Poisson equation
DEFF Research Database (Denmark)
Hejlesen, Mads Mølholm; Rasmussen, Johannes Tophøj; Chatelain, Philippe
2012-01-01
This work improves upon Hockney and Eastwood's Fourier-based algorithm for the unbounded Poisson equation to formally achieve arbitrary high order of convergence without any additional computational cost. We assess the methodology on the kinematic relations between the velocity and vorticity fields....
Coefficient Inverse Problem for Poisson's Equation in a Cylinder
Solov'ev, V. V.
2011-01-01
The inverse problem of determining the coefficient on the right-hand side of Poisson's equation in a cylindrical domain is considered. The Dirichlet boundary value problem is studied. Two types of additional information (overdetermination) can be specified: (i) the trace of the solution to the
Is it safe to use Poisson statistics in nuclear spectrometry?
International Nuclear Information System (INIS)
Pomme, S.; Robouch, P.; Arana, G.; Eguskiza, M.; Maguregui, M.I.
2000-01-01
The boundary conditions in which Poisson statistics can be applied in nuclear spectrometry are investigated. Improved formulas for the uncertainty of nuclear counting with deadtime and pulse pileup are presented. A comparison is made between the expected statistical uncertainty for loss-free counting, fixed live-time and fixed real-time measurements. (author)
Nambu-Poisson reformulation of the finite dimensional dynamical systems
International Nuclear Information System (INIS)
Baleanu, D.; Makhaldiani, N.
1998-01-01
A system of nonlinear ordinary differential equations which in a particular case reduces to Volterra's system is introduced. We found in two simplest cases the complete sets of the integrals of motion using Nambu-Poisson reformulation of the Hamiltonian dynamics. In these cases we have solved the systems by quadratures
A Poisson type formula for Hardy classes on Heisenberg's group
Directory of Open Access Journals (Sweden)
Lopushansky O.V.
2010-06-01
Full Text Available The Hardy type class of complex functions with infinite many variables defined on the Schrodinger irreducible unitary orbit of reduced Heisenberg group, generated by the Gauss density, is investigated. A Poisson integral type formula for their analytic extensions on an open ball is established. Taylor coefficients for analytic extensions are described by the associatedsymmetric Fock space.
Subsonic Flow for the Multidimensional Euler-Poisson System
Bae, Myoungjean; Duan, Ben; Xie, Chunjing
2016-04-01
We establish the existence and stability of subsonic potential flow for the steady Euler-Poisson system in a multidimensional nozzle of a finite length when prescribing the electric potential difference on a non-insulated boundary from a fixed point at the exit, and prescribing the pressure at the exit of the nozzle. The Euler-Poisson system for subsonic potential flow can be reduced to a nonlinear elliptic system of second order. In this paper, we develop a technique to achieve a priori {C^{1,α}} estimates of solutions to a quasi-linear second order elliptic system with mixed boundary conditions in a multidimensional domain enclosed by a Lipschitz continuous boundary. In particular, we discovered a special structure of the Euler-Poisson system which enables us to obtain {C^{1,α}} estimates of the velocity potential and the electric potential functions, and this leads us to establish structural stability of subsonic flows for the Euler-Poisson system under perturbations of various data.
Boundary singularity of Poisson and harmonic Bergman kernels
Czech Academy of Sciences Publication Activity Database
Engliš, Miroslav
2015-01-01
Roč. 429, č. 1 (2015), s. 233-272 ISSN 0022-247X R&D Projects: GA AV ČR IAA100190802 Institutional support: RVO:67985840 Keywords : harmonic Bergman kernel * Poisson kernel * pseudodifferential boundary operators Subject RIV: BA - General Mathematics Impact factor: 1.014, year: 2015 http://www.sciencedirect.com/science/article/pii/S0022247X15003170
Characterization and global analysis of a family of Poisson structures
Energy Technology Data Exchange (ETDEWEB)
Hernandez-Bermejo, Benito [Escuela Superior de Ciencias Experimentales y Tecnologia, Edificio Departamental II, Universidad Rey Juan Carlos, Calle Tulipan S/N, 28933 (Mostoles), Madrid (Spain)]. E-mail: benito.hernandez@urjc.es
2006-06-26
A three-dimensional family of solutions of the Jacobi equations for Poisson systems is characterized. In spite of its general form it is possible the explicit and global determination of its main features, such as the symplectic structure and the construction of the Darboux canonical form. Examples are given.
On covariant Poisson brackets in classical field theory
Energy Technology Data Exchange (ETDEWEB)
Forger, Michael [Instituto de Matemática e Estatística, Universidade de São Paulo, Caixa Postal 66281, BR–05315-970 São Paulo, SP (Brazil); Salles, Mário O. [Instituto de Matemática e Estatística, Universidade de São Paulo, Caixa Postal 66281, BR–05315-970 São Paulo, SP (Brazil); Centro de Ciências Exatas e da Terra, Universidade Federal do Rio Grande do Norte, Campus Universitário – Lagoa Nova, BR–59078-970 Natal, RN (Brazil)
2015-10-15
How to give a natural geometric definition of a covariant Poisson bracket in classical field theory has for a long time been an open problem—as testified by the extensive literature on “multisymplectic Poisson brackets,” together with the fact that all these proposals suffer from serious defects. On the other hand, the functional approach does provide a good candidate which has come to be known as the Peierls–De Witt bracket and whose construction in a geometrical setting is now well understood. Here, we show how the basic “multisymplectic Poisson bracket” already proposed in the 1970s can be derived from the Peierls–De Witt bracket, applied to a special class of functionals. This relation allows to trace back most (if not all) of the problems encountered in the past to ambiguities (the relation between differential forms on multiphase space and the functionals they define is not one-to-one) and also to the fact that this class of functionals does not form a Poisson subalgebra.
Poisson sampling - The adjusted and unadjusted estimator revisited
Michael S. Williams; Hans T. Schreuder; Gerardo H. Terrazas
1998-01-01
The prevailing assumption, that for Poisson sampling the adjusted estimator "Y-hat a" is always substantially more efficient than the unadjusted estimator "Y-hat u" , is shown to be incorrect. Some well known theoretical results are applicable since "Y-hat a" is a ratio-of-means estimator and "Y-hat u" a simple unbiased estimator...
Pricing Zero-Coupon Catastrophe Bonds Using EVT with Doubly Stochastic Poisson Arrivals
Directory of Open Access Journals (Sweden)
Zonggang Ma
2017-01-01
Full Text Available The frequency and severity of climate abnormal change displays an irregular upward cycle as global warming intensifies. Therefore, this paper employs a doubly stochastic Poisson process with Black Derman Toy (BDT intensity to describe the catastrophic characteristics. By using the Property Claim Services (PCS loss index data from 2001 to 2010 provided by the US Insurance Services Office (ISO, the empirical result reveals that the BDT arrival rate process is superior to the nonhomogeneous Poisson and lognormal intensity process due to its smaller RMSE, MAE, MRPE, and U and larger E and d. Secondly, to depict extreme features of catastrophic risks, this paper adopts the Peak Over Threshold (POT in extreme value theory (EVT to characterize the tail characteristics of catastrophic loss distribution. And then the loss distribution is analyzed and assessed using a quantile-quantile (QQ plot to visually check whether the PCS index observations meet the generalized Pareto distribution (GPD assumption. Furthermore, this paper derives a pricing formula for zero-coupon catastrophe bonds with a stochastic interest rate environment and aggregate losses generated by a compound doubly stochastic Poisson process under the forward measure. Finally, simulation results verify pricing model predictions and show how catastrophic risks and interest rate risk affect the prices of zero-coupon catastrophe bonds.
Extremal Properties of an Intermittent Poisson Process Generating 1/f Noise
Grüneis, Ferdinand
2016-08-01
It is well-known that the total power of a signal exhibiting a pure 1/f shape is divergent. This phenomenon is also called the infrared catastrophe. Mandelbrot claims that the infrared catastrophe can be overcome by stochastic processes which alternate between active and quiescent states. We investigate an intermittent Poisson process (IPP) which belongs to the family of stochastic processes suggested by Mandelbrot. During the intermission δ (quiescent period) the signal is zero. The active period is divided into random intervals of mean length τ0 consisting of a fluctuating number of events; this is giving rise to so-called clusters. The advantage of our treatment is that the spectral features of the IPP can be derived analytically. Our considerations are focused on the case that intermission is only a small disturbance of the Poisson process, i.e., to the case that δ ≤ τ0. This makes it difficult or even impossible to discriminate a spike train of such an IPP from that of a Poisson process. We investigate the conditions under which a 1/f spectrum can be observed. It is shown that 1/f noise generated by the IPP is accompanied with extreme variance. In agreement with the considerations of Mandelbrot, the IPP avoids the infrared catastrophe. Spectral analysis of the simulated IPP confirms our theoretical results. The IPP is a model for an almost random walk generating both white and 1/f noise and can be applied for an interpretation of 1/f noise in metallic resistors.
Poisson traces, D-modules, and symplectic resolutions
Etingof, Pavel; Schedler, Travis
2018-03-01
We survey the theory of Poisson traces (or zeroth Poisson homology) developed by the authors in a series of recent papers. The goal is to understand this subtle invariant of (singular) Poisson varieties, conditions for it to be finite-dimensional, its relationship to the geometry and topology of symplectic resolutions, and its applications to quantizations. The main technique is the study of a canonical D-module on the variety. In the case the variety has finitely many symplectic leaves (such as for symplectic singularities and Hamiltonian reductions of symplectic vector spaces by reductive groups), the D-module is holonomic, and hence, the space of Poisson traces is finite-dimensional. As an application, there are finitely many irreducible finite-dimensional representations of every quantization of the variety. Conjecturally, the D-module is the pushforward of the canonical D-module under every symplectic resolution of singularities, which implies that the space of Poisson traces is dual to the top cohomology of the resolution. We explain many examples where the conjecture is proved, such as symmetric powers of du Val singularities and symplectic surfaces and Slodowy slices in the nilpotent cone of a semisimple Lie algebra. We compute the D-module in the case of surfaces with isolated singularities and show it is not always semisimple. We also explain generalizations to arbitrary Lie algebras of vector fields, connections to the Bernstein-Sato polynomial, relations to two-variable special polynomials such as Kostka polynomials and Tutte polynomials, and a conjectural relationship with deformations of symplectic resolutions. In the appendix we give a brief recollection of the theory of D-modules on singular varieties that we require.
A random matrix approach to the crossover of energy-level statistics from Wigner to Poisson
International Nuclear Information System (INIS)
Datta, Nilanjana; Kunz, Herve
2004-01-01
We analyze a class of parametrized random matrix models, introduced by Rosenzweig and Porter, which is expected to describe the energy level statistics of quantum systems whose classical dynamics varies from regular to chaotic as a function of a parameter. We compute the generating function for the correlations of energy levels, in the limit of infinite matrix size. The crossover between Poisson and Wigner statistics is measured by a renormalized coupling constant. The model is exactly solved in the sense that, in the limit of infinite matrix size, the energy-level correlation functions and their generating function are given in terms of a finite set of integrals
Invariants and labels for Lie-Poisson Systems
International Nuclear Information System (INIS)
Thiffeault, J.L.; Morrison, P.J.
1998-04-01
Reduction is a process that uses symmetry to lower the order of a Hamiltonian system. The new variables in the reduced picture are often not canonical: there are no clear variables representing positions and momenta, and the Poisson bracket obtained is not of the canonical type. Specifically, we give two examples that give rise to brackets of the noncanonical Lie-Poisson form: the rigid body and the two-dimensional ideal fluid. From these simple cases, we then use the semidirect product extension of algebras to describe more complex physical systems. The Casimir invariants in these systems are examined, and some are shown to be linked to the recovery of information about the configuration of the system. We discuss a case in which the extension is not a semidirect product, namely compressible reduced MHD, and find for this case that the Casimir invariants lend partial information about the configuration of the system
Reference manual for the POISSON/SUPERFISH Group of Codes
Energy Technology Data Exchange (ETDEWEB)
1987-01-01
The POISSON/SUPERFISH Group codes were set up to solve two separate problems: the design of magnets and the design of rf cavities in a two-dimensional geometry. The first stage of either problem is to describe the layout of the magnet or cavity in a way that can be used as input to solve the generalized Poisson equation for magnets or the Helmholtz equations for cavities. The computer codes require that the problems be discretized by replacing the differentials (dx,dy) by finite differences ({delta}X,{delta}Y). Instead of defining the function everywhere in a plane, the function is defined only at a finite number of points on a mesh in the plane.
Bering's proposal for boundary contribution to the Poisson bracket
International Nuclear Information System (INIS)
Soloviev, V.O.
1998-11-01
It is shown that the Poisson bracket with boundary terms recently proposed by Bering can be deduced from the Poisson bracket proposed by the present author if one omits terms free of Euler-Lagrange derivatives (''annihilation principle''). This corresponds to another definition of the formal product of distributions (or, saying it in other words, to another definition of the pairing between 1-forms and 1-vectors in the formal variational calculus). We extend the formula initially suggested by Bering only for the ultralocal case with constant coefficients onto the general non-ultralocal brackets with coefficients depending on fields and their spatial derivatives. The lack of invariance under changes of dependent variables (field redefinitions) seems a drawback of this proposal. (author)
An adaptive fast multipole accelerated Poisson solver for complex geometries
Askham, T.; Cerfon, A. J.
2017-09-01
We present a fast, direct and adaptive Poisson solver for complex two-dimensional geometries based on potential theory and fast multipole acceleration. More precisely, the solver relies on the standard decomposition of the solution as the sum of a volume integral to account for the source distribution and a layer potential to enforce the desired boundary condition. The volume integral is computed by applying the FMM on a square box that encloses the domain of interest. For the sake of efficiency and convergence acceleration, we first extend the source distribution (the right-hand side in the Poisson equation) to the enclosing box as a C0 function using a fast, boundary integral-based method. We demonstrate on multiply connected domains with irregular boundaries that this continuous extension leads to high accuracy without excessive adaptive refinement near the boundary and, as a result, to an extremely efficient "black box" fast solver.
Monitoring Poisson time series using multi-process models
DEFF Research Database (Denmark)
Engebjerg, Malene Dahl Skov; Lundbye-Christensen, Søren; Kjær, Birgitte B.
Surveillance of infectious diseases based on routinely collected public health data is important for at least three reasons: The early detection of an epidemic may facilitate prompt interventions and the seasonal variations and long term trend may be of general epidemiological interest. Furthermore...
Current and Predicted Fertility using Poisson Regression Model ...
African Journals Online (AJOL)
AJRH Managing Editor
marriage, modern contraceptive use, paid employment status, marital status, marital duration, education attainment, husbands education attainment, residence, zones, wealth quintiles. Children ever born in the context of this study refers to the number of children a woman previously born alive as at the time of the study.
A one-level FETI method for the drift–diffusion-Poisson system with discontinuities at an interface
Baumgartner, Stefan
2013-06-01
A 3d feti method for the drift-diffusion-Poisson system including discontinuities at a 2d interface is developed. The motivation for this work is to provide a parallel numerical algorithm for a system of PDEs that are the basic model equations for the simulation of semiconductor devices such as transistors and sensors. Moreover, discontinuities or jumps in the potential and its normal derivative at a 2d surface are included for the simulation of nanowire sensors based on a homogenized model. Using the feti method, these jump conditions can be included with the usual numerical properties and the original Farhat-Roux feti method is extended to the drift-diffusion-Poisson equations including discontinuities. We show two numerical examples. The first example verifies the correct implementation including the discontinuities on a 2d grid divided into eight subdomains. The second example is 3d and shows the application of the algorithm to the simulation of nanowire sensors with high aspect ratios. The Poisson-Boltzmann equation and the drift-diffusion-Poisson system with jump conditions are solved on a 3d grid with real-world boundary conditions. © 2013 Elsevier Inc..
Estimating small signals by using maximum likelihood and Poisson statistics
Hannam, M D
1999-01-01
Estimation of small signals from counting experiments with backgrounds larger than signals is solved using maximum likelihood estimation for situations in which both signal and background statistics are Poissonian. Confidence levels are discussed, and Poisson, Gauss and least-squares fitting methods are compared. Efficient algorithms that estimate signal strengths and confidence levels are devised for computer implementation. Examples from simulated data and a low count rate experiment in nuclear physics are given. (author)
Stress Calculation of a TRISO Coated Particle Fuel by Using a Poisson's Ratio in Creep Condition
International Nuclear Information System (INIS)
Cho, Moon-Sung; Kim, Y. M.; Lee, Y. W.; Jeong, K. C.; Kim, Y. K.; Oh, S. C.; Kim, W. K.
2007-01-01
KAERI, which has been carrying out the Korean VHTR (Very High Temperature modular gas cooled Reactor) project since 2004, has been developing a performance analysis code for the TRISO coated particle fuel named COPA (COated Particle fuel Analysis). COPA predicts temperatures, stresses, a fission gas release and failure probabilities of a coated particle fuel in normal operating conditions. KAERI, on the other hand, is developing an ABAQUS based finite element(FE) model to cover the non-linear behaviors of a coated particle fuel such as cracking or debonding of the TRISO coating layers. Using the ABAQUS based FE model, verification calculations were carried out for the IAEA CRP-6 benchmark problems involving creep, swelling, and pressure. However, in this model the Poisson's ratio for elastic solution was used for creep strain calculation. In this study, an improvement is made for the ABAQUS based finite element model by using the Poisson's ratio in creep condition for the calculation of the creep strain rate. As a direct input of the coefficient in a creep condition is impossible, a user subroutine for the ABAQUS solution is prepared in FORTRAN for use in the calculations of the creep strain of the coating layers in the radial and hoop directions of the spherical fuel. This paper shows the calculation results of a TRISO coated particle fuel subject to an irradiation condition assumed as in the Miller's publication in comparison with the results obtained from the old FE model used in the CRP-6 benchmark calculations
Multilevel Methods for the Poisson-Boltzmann Equation
Holst, Michael Jay
We consider the numerical solution of the Poisson -Boltzmann equation (PBE), a three-dimensional second order nonlinear elliptic partial differential equation arising in biophysics. This problem has several interesting features impacting numerical algorithms, including discontinuous coefficients representing material interfaces, rapid nonlinearities, and three spatial dimensions. Similar equations occur in various applications, including nuclear physics, semiconductor physics, population genetics, astrophysics, and combustion. In this thesis, we study the PBE, discretizations, and develop multilevel-based methods for approximating the solutions of these types of equations. We first outline the physical model and derive the PBE, which describes the electrostatic potential of a large complex biomolecule lying in a solvent. We next study the theoretical properties of the linearized and nonlinear PBE using standard function space methods; since this equation has not been previously studied theoretically, we provide existence and uniqueness proofs in both the linearized and nonlinear cases. We also analyze box-method discretizations of the PBE, establishing several properties of the discrete equations which are produced. In particular, we show that the discrete nonlinear problem is well-posed. We study and develop linear multilevel methods for interface problems, based on algebraic enforcement of Galerkin or variational conditions, and on coefficient averaging procedures. Using a stencil calculus, we show that in certain simplified cases the two approaches are equivalent, with different averaging procedures corresponding to different prolongation operators. We also develop methods for nonlinear problems based on a nonlinear multilevel method, and on linear multilevel methods combined with a globally convergent damped-inexact-Newton method. We derive a necessary and sufficient descent condition for the inexact-Newton direction, enabling the development of extremely
Poisson-Like Spiking in Circuits with Probabilistic Synapses
Moreno-Bote, Rubén
2014-01-01
Neuronal activity in cortex is variable both spontaneously and during stimulation, and it has the remarkable property that it is Poisson-like over broad ranges of firing rates covering from virtually zero to hundreds of spikes per second. The mechanisms underlying cortical-like spiking variability over such a broad continuum of rates are currently unknown. We show that neuronal networks endowed with probabilistic synaptic transmission, a well-documented source of variability in cortex, robustly generate Poisson-like variability over several orders of magnitude in their firing rate without fine-tuning of the network parameters. Other sources of variability, such as random synaptic delays or spike generation jittering, do not lead to Poisson-like variability at high rates because they cannot be sufficiently amplified by recurrent neuronal networks. We also show that probabilistic synapses predict Fano factor constancy of synaptic conductances. Our results suggest that synaptic noise is a robust and sufficient mechanism for the type of variability found in cortex. PMID:25032705
Brain, music, and non-Poisson renewal processes
Bianco, Simone; Ignaccolo, Massimiliano; Rider, Mark S.; Ross, Mary J.; Winsor, Phil; Grigolini, Paolo
2007-06-01
In this paper we show that both music composition and brain function, as revealed by the electroencephalogram (EEG) analysis, are renewal non-Poisson processes living in the nonergodic dominion. To reach this important conclusion we process the data with the minimum spanning tree method, so as to detect significant events, thereby building a sequence of times, which is the time series to analyze. Then we show that in both cases, EEG and music composition, these significant events are the signature of a non-Poisson renewal process. This conclusion is reached using a technique of statistical analysis recently developed by our group, the aging experiment (AE). First, we find that in both cases the distances between two consecutive events are described by nonexponential histograms, thereby proving the non-Poisson nature of these processes. The corresponding survival probabilities Ψ(t) are well fitted by stretched exponentials [ Ψ(t)∝exp (-(γt)α) , with 0.5music composition yield μmusic on the human brain.
Optimal smoothing of poisson degraded nuclear medicine image data
International Nuclear Information System (INIS)
Hull, D.M.
1985-01-01
The development of a method that removes Poisson noise from nuclear medicine studies will have significant impact on the quantitative analysis and clinical reliability of these data. The primary objective of the work described in this thesis was to develop a linear, non-stationary optimal filter to reduce Poisson noise. The derived filter is automatically calculated from a large group (library) of similar patient studies representing all similarly acquired studies (the ensemble). The filter design was evaluated under controlled conditions using two computer simulated ensembles, devised to represent selected properties of real patient gated blood pool studies. Fortran programs were developed to generate libraries of Poisson degraded simulated studies for each ensemble. These libraries then were used to estimate optimal filters specific to the ensemble. Libraries of previously acquired patient gated blood pool studies then were used to estimate the optimal filters for an ensemble of similarly acquired gated blood pool studies. These filters were applied to studies of 13 patients who received multiple repeat studies at one time. Comparisons of both the filtered and raw data to averages of the repeat studies demonstrated that the optimal filters, calculated from a library of 800 studies, reduce the mean square error in the patient data by 60%. It is expected that optimally filtered gated blood pool studies will improve quantitative analysis of the data
Blind beam-hardening correction from Poisson measurements
Gu, Renliang; Dogandžić, Aleksandar
2016-02-01
We develop a sparse image reconstruction method for Poisson-distributed polychromatic X-ray computed tomography (CT) measurements under the blind scenario where the material of the inspected object and the incident energy spectrum are unknown. We employ our mass-attenuation spectrum parameterization of the noiseless measurements and express the mass- attenuation spectrum as a linear combination of B-spline basis functions of order one. A block coordinate-descent algorithm is developed for constrained minimization of a penalized Poisson negative log-likelihood (NLL) cost function, where constraints and penalty terms ensure nonnegativity of the spline coefficients and nonnegativity and sparsity of the density map image; the image sparsity is imposed using a convex total-variation (TV) norm penalty term. This algorithm alternates between a Nesterov's proximal-gradient (NPG) step for estimating the density map image and a limited-memory Broyden-Fletcher-Goldfarb-Shanno with box constraints (L-BFGS-B) step for estimating the incident-spectrum parameters. To accelerate convergence of the density- map NPG steps, we apply function restart and a step-size selection scheme that accounts for varying local Lipschitz constants of the Poisson NLL. Real X-ray CT reconstruction examples demonstrate the performance of the proposed scheme.
Application of the Poisson-Nernst-Planck equations to the migration test
DEFF Research Database (Denmark)
Krabbenhøft, Kristian; Krabbenhøft, Jørgen
2008-01-01
The Poisson-Nernst-Planck (PNP) equations are applied to model the migration test. A detailed analysis of the equations is presented and the effects of a number of common, simplifying assumptions are quantified. In addition, closed-form solutions for the effective chloride diffusivity based...... on the full PNP equations are derived, a number of experiments are analyzed in detail, and a new, truly accelerated migration test is proposed. Finally, we present a finite element procedure for numerical solution of the PNP equations....
Filling of a Poisson trap by a population of random intermittent searchers
Bressloff, Paul C.
2012-03-01
We extend the continuum theory of random intermittent search processes to the case of N independent searchers looking to deliver cargo to a single hidden target located somewhere on a semi-infinite track. Each searcher randomly switches between a stationary state and either a leftward or rightward constant velocity state. We assume that all of the particles start at one end of the track and realize sample trajectories independently generated from the same underlying stochastic process. The hidden target is treated as a partially absorbing trap in which a particle can only detect the target and deliver its cargo if it is stationary and within range of the target; the particle is removed from the system after delivering its cargo. As a further generalization of previous models, we assume that up to n successive particles can find the target and deliver its cargo. Assuming that the rate of target detection scales as 1/N, we show that there exists a well-defined mean-field limit N→ in which the stochastic model reduces to a deterministic system of linear reaction-hyperbolic equations for the concentrations of particles in each of the internal states. These equations decouple from the stochastic process associated with filling the target with cargo. The latter can be modeled as a Poisson process in which the time-dependent rate of filling λ(t) depends on the concentration of stationary particles within the target domain. Hence, we refer to the target as a Poisson trap. We analyze the efficiency of filling the Poisson trap with n particles in terms of the waiting time density f n(t). The latter is determined by the integrated Poisson rate μ(t)=0tλ(s)ds, which in turn depends on the solution to the reaction-hyperbolic equations. We obtain an approximate solution for the particle concentrations by reducing the system of reaction-hyperbolic equations to a scalar advection-diffusion equation using a quasisteady-state analysis. We compare our analytical results for the
Action-angle variables and a KAM theorem for b-Poisson manifolds
Kiesenhofer, Anna; Miranda Galcerán, Eva; Scott, Geoffrey
2015-01-01
In this article we prove an action-angle theorem for b-integrable systems on b-Poisson manifolds improving the action-angle theorem contained in [14] for general Poisson manifolds in this setting. As an application, we prove a KAM-type theorem for b-Poisson manifolds. (C) 2015 Elsevier Masson SAS. All rights reserved.
A Raikov-Type Theorem for Radial Poisson Distributions: A Proof of Kingman's Conjecture
Van Nguyen, Thu
2011-01-01
In the present paper we prove the following conjecture in Kingman, J.F.C., Random walks with spherical symmetry, Acta Math.,109, (1963), 11-53. concerning a famous Raikov's theorem of decomposition of Poisson random variables: "If a radial sum of two independent random variables X and Y is radial Poisson, then each of them must be radial Poisson."
Gajda, Dorota; Guihenneuc-Jouyaux, Chantal; Rousseau, Judith; Mengersen, Kerrie,; Nur, Darfiana
2010-01-01
International audience; Abstract: The Importance Sampling method is used as an alternative approach to MCMC in repeated Bayesian estimations. In the particular context of numerous data sets, MCMC algorithms have to be called on several times which may become computationally expensive. Since Importance Sampling requires a sample from a posteriodistribution, our idea is to use MCMC to generate only a certain number of Markov chains and use them later in the subsequent IS estimations. For each I...
Okawa, S; Endo, Y; Hoshi, Y; Yamada, Y
2012-01-01
A method to reduce noise for time-domain diffuse optical tomography (DOT) is proposed. Poisson noise which contaminates time-resolved photon counting data is reduced by use of maximum a posteriori estimation. The noise-free data are modeled as a Markov random process, and the measured time-resolved data are assumed as Poisson distributed random variables. The posterior probability of the occurrence of the noise-free data is formulated. By maximizing the probability, the noise-free data are estimated, and the Poisson noise is reduced as a result. The performances of the Poisson noise reduction are demonstrated in some experiments of the image reconstruction of time-domain DOT. In simulations, the proposed method reduces the relative error between the noise-free and noisy data to about one thirtieth, and the reconstructed DOT image was smoothed by the proposed noise reduction. The variance of the reconstructed absorption coefficients decreased by 22% in a phantom experiment. The quality of DOT, which can be applied to breast cancer screening etc., is improved by the proposed noise reduction.
Directory of Open Access Journals (Sweden)
Young-Doo Kwon
2014-08-01
Full Text Available A finite element procedure is presented for the analysis of rubber-like hyperelastic materials. The volumetric incompressibility condition of rubber deformation is included in the formulation using the penalty method, while the principle of virtual work is used to derive a nonlinear finite element equation for the large displacement problem that is presented in a total-Lagrangian description. The behavior of rubber deformation is represented by hyperelastic constitutive relations based on a generalized Mooney-Rivlin model. The proposed finite element procedure using analytic differentiation exhibited results that matched very well with those from the well-known commercial packages NISA II and ABAQUS. Furthermore, the convergence of equilibrium iteration is quite slow or frequently fails in the case of near-incompressible rubber. To prevent such phenomenon even for the case that Poisson's ratio is very close to 0.5, Poisson's ratio of 0.49000 is used, first, to get an approximate solution without any difficulty; then the applied load is maintained and Poisson's ratio is increased to 0.49999 following a proposed pattern and adopting a technique of relaxation by monitoring the convergence rate. For a given Poisson ratio near 0.5, with this approach, we could reduce the number of substeps considerably.
Botello-Smith, Wesley M; Luo, Ray
2015-10-26
Continuum solvent models have been widely used in biomolecular modeling applications. Recently much attention has been given to inclusion of implicit membranes into existing continuum Poisson-Boltzmann solvent models to extend their applications to membrane systems. Inclusion of an implicit membrane complicates numerical solutions of the underlining Poisson-Boltzmann equation due to the dielectric inhomogeneity on the boundary surfaces of a computation grid. This can be alleviated by the use of the periodic boundary condition, a common practice in electrostatic computations in particle simulations. The conjugate gradient and successive over-relaxation methods are relatively straightforward to be adapted to periodic calculations, but their convergence rates are quite low, limiting their applications to free energy simulations that require a large number of conformations to be processed. To accelerate convergence, the Incomplete Cholesky preconditioning and the geometric multigrid methods have been extended to incorporate periodicity for biomolecular applications. Impressive convergence behaviors were found as in the previous applications of these numerical methods to tested biomolecules and MMPBSA calculations.
Generating clustered scale-free networks using Poisson based localization of edges
Türker, İlker
2018-05-01
We introduce a variety of network models using a Poisson-based edge localization strategy, which result in clustered scale-free topologies. We first verify the success of our localization strategy by realizing a variant of the well-known Watts-Strogatz model with an inverse approach, implying a small-world regime of rewiring from a random network through a regular one. We then apply the rewiring strategy to a pure Barabasi-Albert model and successfully achieve a small-world regime, with a limited capacity of scale-free property. To imitate the high clustering property of scale-free networks with higher accuracy, we adapted the Poisson-based wiring strategy to a growing network with the ingredients of both preferential attachment and local connectivity. To achieve the collocation of these properties, we used a routine of flattening the edges array, sorting it, and applying a mixing procedure to assemble both global connections with preferential attachment and local clusters. As a result, we achieved clustered scale-free networks with a computational fashion, diverging from the recent studies by following a simple but efficient approach.
Directory of Open Access Journals (Sweden)
Dongkyun Kim
2014-01-01
Full Text Available A novel approach for a Poisson cluster stochastic rainfall generator was validated in its ability to reproduce important rainfall and watershed response characteristics at 104 locations in the United States. The suggested novel approach, The Hybrid Model (THM, as compared to the traditional Poisson cluster rainfall modeling approaches, has an additional capability to account for the interannual variability of rainfall statistics. THM and a traditional approach of Poisson cluster rainfall model (modified Bartlett-Lewis rectangular pulse model were compared in their ability to reproduce the characteristics of extreme rainfall and watershed response variables such as runoff and peak flow. The results of the comparison indicate that THM generally outperforms the traditional approach in reproducing the distributions of peak rainfall, peak flow, and runoff volume. In addition, THM significantly outperformed the traditional approach in reproducing extreme rainfall by 2.3% to 66% and extreme flow values by 32% to 71%.
Bases chimiosensorielles du comportement alimentaire chez les poissons
Directory of Open Access Journals (Sweden)
SAGLIO Ph.
1981-07-01
Full Text Available Le comportement alimentaire, indispensable à la survie de l'individu et donc de l'espèce, occupe à ce titre une position de première importance dans la hiérarchie des comportements fondamentaux qui tous en dépendent très étroitement. Chez les poissons, cette prééminence se trouve illustrée par l'extrême diversité des supports sensoriels impliqués et des expressions comportementales qui leur sont liées. A la suite d'un certain nombre de mises en évidence neurophysiologiques et éthologiques de l'importance du sens chimique (olfaction, gustation dans le comportement alimentaire des poissons, de très importants secteurs d'études électrophysiologiques et d'analyses physico-chimiques visant à en déterminer la nature exacte (en termes de substances actives se sont développés ces vingt dernières années. De tous ces travaux dont les plus avancés sont présentés ici, il ressort que les acides aminés de série L plus ou moins associés à d'autres composés de poids moléculaires < 1000 constituent des composés chimiques jouant un rôle déterminant dans le comportement alimentaire de nombreuses espèces de poissons carnivores.
Comment on: 'A Poisson resampling method for simulating reduced counts in nuclear medicine images'
DEFF Research Database (Denmark)
de Nijs, Robin
2015-01-01
by a direct numerical simulation in Matlab. Not only Poisson resampling, but also two direct redrawing methods were investigated. Redrawing methods were based on a Poisson and a Gaussian distribution. Mean, standard deviation, skewness and excess kurtosis half-count/full-count ratios were determined for all...... methods, and compared to the theoretical values for a Poisson distribution. Statistical parameters showed the same behavior as in the original note and showed the superiority of the Poisson resampling method. Rounding off before saving of the half count image had a severe impact on counting statistics...... for counts below 100. Only Poisson resampling was not affected by this, while Gaussian redrawing was less affected by it than Poisson redrawing. Poisson resampling is the method of choice, when simulating half-count (or less) images from full-count images. It simulates correctly the statistical properties...
Localization of Point Sources for Poisson Equation using State Observers
Majeed, Muhammad Usman
2016-08-09
A method based On iterative observer design is presented to solve point source localization problem for Poisson equation with riven boundary data. The procedure involves solution of multiple boundary estimation sub problems using the available Dirichlet and Neumann data from different parts of the boundary. A weighted sum of these solution profiles of sub-problems localizes point sources inside the domain. Method to compute these weights is also provided. Numerical results are presented using finite differences in a rectangular domain. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Ruin probabilities for a regenerative Poisson gap generated risk process
DEFF Research Database (Denmark)
Asmussen, Søren; Biard, Romain
. Asymptotic expressions for the inﬁnite horizon ruin probabilities are given both for the light- and the heavy-tailed case. A basic observation is that the process regenerates at each G-claim. Also an approach via Markov additive processes is outlined, and heuristics are given for the distribution of the time......A risk process with constant premium rate c and Poisson arrivals of claims is considered. A threshold r is deﬁned for claim interarrival times, such that if k consecutive interarrival times are larger than r, then the next claim has distribution G. Otherwise, the claim size distribution is F...
Standard Test Method for Determining Poisson's Ratio of Honeycomb Cores
American Society for Testing and Materials. Philadelphia
2002-01-01
1.1 This test method covers the determination of the honeycomb Poisson's ratio from the anticlastic curvature radii, see . 1.2 The values stated in SI units are to be regarded as the standard. The inch-pound units given may be approximate. This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.
Maslov indices, Poisson brackets, and singular differential forms
Esterlis, I.; Haggard, H. M.; Hedeman, A.; Littlejohn, R. G.
2014-06-01
Maslov indices are integers that appear in semiclassical wave functions and quantization conditions. They are often notoriously difficult to compute. We present methods of computing the Maslov index that rely only on typically elementary Poisson brackets and simple linear algebra. We also present a singular differential form, whose integral along a curve gives the Maslov index of that curve. The form is closed but not exact, and transforms by an exact differential under canonical transformations. We illustrate the method with the 6j-symbol, which is important in angular-momentum theory and in quantum gravity.
Gap processing for adaptive maximal poisson-disk sampling
Yan, Dongming
2013-10-17
In this article, we study the generation of maximal Poisson-disk sets with varying radii. First, we present a geometric analysis of gaps in such disk sets. This analysis is the basis for maximal and adaptive sampling in Euclidean space and on manifolds. Second, we propose efficient algorithms and data structures to detect gaps and update gaps when disks are inserted, deleted, moved, or when their radii are changed.We build on the concepts of regular triangulations and the power diagram. Third, we show how our analysis contributes to the state-of-the-art in surface remeshing. © 2013 ACM.
DEFF Research Database (Denmark)
Kirkeby, Carsten Thure; Hisham Beshara Halasa, Tariq; Gussmann, Maya Katrin
2017-01-01
Precise estimates of disease transmission rates are critical for epidemiological simulation models. Most often these rates must be estimated from longitudinal field data, which are costly and time-consuming to conduct. Consequently, measures to reduce cost like increased sampling intervals...... or subsampling of the population are implemented. To assess the impact of such measures we implement two different SIS models to simulate disease transmission: A simple closed population model and a realistic dairy herd including population dynamics. We analyze the accuracy of different methods for estimating...... the transmission rate. We use data from the two simulation models and vary the sampling intervals and the size of the population sampled. We devise two new methods to determine transmission rate, and compare these to the frequently used Poisson regression method in both epidemic and endemic situations. For most...
A Spline-Based Lack-Of-Fit Test for Independent Variable Effect in Poisson Regression.
Li, Chin-Shang; Tu, Wanzhu
2007-05-01
In regression analysis of count data, independent variables are often modeled by their linear effects under the assumption of log-linearity. In reality, the validity of such an assumption is rarely tested, and its use is at times unjustifiable. A lack-of-fit test is proposed for the adequacy of a postulated functional form of an independent variable within the framework of semiparametric Poisson regression models based on penalized splines. It offers added flexibility in accommodating the potentially non-loglinear effect of the independent variable. A likelihood ratio test is constructed for the adequacy of the postulated parametric form, for example log-linearity, of the independent variable effect. Simulations indicate that the proposed model performs well, and misspecified parametric model has much reduced power. An example is given.
Non linear Euler-Poisson system. Part 1: global existence of low entropy solutions
International Nuclear Information System (INIS)
Cordier, S.
1995-05-01
In this work a 1-D model of electrons and ions plasma is considered. Electrons are supposed to be in Maxwell-Boltzmann thermodynamic equilibrium while ions are described with an isothermal flow model of charged particles submitted to a self-consistent electric field. A collision term between neutral particles and ions simulates the presence of neutral particles. This work demonstrates the existence of low entropy solutions for this simple model with arbitrary initial conditions. Most of the paper is devoted to the demonstration of this theorem and follows the successive steps: construction of a numerical scheme, recall of the classical properties of Riemann problem solutions using Glimm method, uniform estimations for the whole variation norm, and finally, convergence of the constructed solutions towards a low entropy solution for the non-linear Euler/Poisson system. Domains of application for this type of model are listed in the conclusion. (J.S.). 18 refs
Liu, Xingping; Wang, Changhao; Wang, Jun; Li, Zhilin; Zhao, Hongkai; Luo, Ray
2013-01-07
Continuum solvent treatments based on the Poisson-Boltzmann equation have been widely accepted for energetic analysis of biomolecular systems. In these approaches, the molecular solute is treated as a low dielectric region and the solvent is treated as a high dielectric continuum. The existence of a sharp dielectric jump at the solute-solvent interface poses a challenge to model the solvation energetics accurately with such a simple mathematical model. In this study, we explored and evaluated a strategy based on the "induced surface charge" to eliminate the dielectric jump within the finite-difference discretization scheme. In addition to the use of the induced surface charges in solving the equation, the second-order accurate immersed interface method is also incorporated to discretize the equation. The resultant linear system is solved with the GMRES algorithm to explicitly impose the flux conservation condition across the solvent-solute interface. The new strategy was evaluated on both analytical and realistic biomolecular systems. The numerical tests demonstrate the feasibility of utilizing induced surface charge in the finite-difference solution of the Poisson-Boltzmann equation. The analysis data further show that the strategy is consistent with theory and the classical finite-difference method on the tested systems. Limitations of the current implementations and further improvements are also analyzed and discussed to fully bring out its potential of achieving higher numerical accuracy.
Inexact Bregman iteration with an application to Poisson data reconstruction
Benfenati, A.; Ruggiero, V.
2013-06-01
This work deals with the solution of image restoration problems by an iterative regularization method based on the Bregman iteration. Any iteration of this scheme requires the exact computation of the minimizer of a function. However, in some image reconstruction applications, it is either impossible or extremely expensive to obtain exact solutions of these subproblems. In this paper, we propose an inexact version of the iterative procedure, where the inexactness in the inner subproblem solution is controlled by a criterion that preserves the convergence of the Bregman iteration and its features in image restoration problems. In particular, the method allows us to obtain accurate reconstructions also when only an overestimation of the regularization parameter is known. The introduction of the inexactness in the iterative scheme allows us to address image reconstruction problems from data corrupted by Poisson noise, exploiting the recent advances about specialized algorithms for the numerical minimization of the generalized Kullback-Leibler divergence combined with a regularization term. The results of several numerical experiments enable us to evaluate the proposed scheme for image deblurring or denoising in the presence of Poisson noise.
A modified Poisson-Boltzmann equation applied to protein adsorption.
Gama, Marlon de Souza; Santos, Mirella Simões; Lima, Eduardo Rocha de Almeida; Tavares, Frederico Wanderley; Barreto, Amaro Gomes Barreto
2018-01-05
Ion-exchange chromatography has been widely used as a standard process in purification and analysis of protein, based on the electrostatic interaction between the protein and the stationary phase. Through the years, several approaches are used to improve the thermodynamic description of colloidal particle-surface interaction systems, however there are still a lot of gaps specifically when describing the behavior of protein adsorption. Here, we present an improved methodology for predicting the adsorption equilibrium constant by solving the modified Poisson-Boltzmann (PB) equation in bispherical coordinates. By including dispersion interactions between ions and protein, and between ions and surface, the modified PB equation used can describe the Hofmeister effects. We solve the modified Poisson-Boltzmann equation to calculate the protein-surface potential of mean force, treated as spherical colloid-plate system, as a function of process variables. From the potential of mean force, the Henry constants of adsorption, for different proteins and surfaces, are calculated as a function of pH, salt concentration, salt type, and temperature. The obtained Henry constants are compared with experimental data for several isotherms showing excellent agreement. We have also performed a sensitivity analysis to verify the behavior of different kind of salts and the Hofmeister effects. Copyright © 2017 Elsevier B.V. All rights reserved.
A Tubular Biomaterial Construct Exhibiting a Negative Poisson's Ratio.
Directory of Open Access Journals (Sweden)
Jin Woo Lee
Full Text Available Developing functional small-diameter vascular grafts is an important objective in tissue engineering research. In this study, we address the problem of compliance mismatch by designing and developing a 3D tubular construct that has a negative Poisson's ratio νxy (NPR. NPR constructs have the unique ability to expand transversely when pulled axially, thereby resulting in a highly-compliant tubular construct. In this work, we used projection stereolithography to 3D-print a planar NPR sheet composed of photosensitive poly(ethylene glycol diacrylate biomaterial. We used a step-lithography exposure and a stitch process to scale up the projection printing process, and used the cut-missing rib unit design to develop a centimeter-scale NPR sheet, which was rolled up to form a tubular construct. The constructs had Poisson's ratios of -0.6 ≤ νxy ≤ -0.1. The NPR construct also supports higher cellular adhesion than does the construct that has positive νxy. Our NPR design offers a significant advance in the development of highly-compliant vascular grafts.
Chang, Yu-Wei; Tsong, Yi; Zhao, Zhigen
2017-01-01
Assessing equivalence or similarity has drawn much attention recently as many drug products have lost or will lose their patents in the next few years, especially certain best-selling biologics. To claim equivalence between the test treatment and the reference treatment when assay sensitivity is well established from historical data, one has to demonstrate both superiority of the test treatment over placebo and equivalence between the test treatment and the reference treatment. Thus, there is urgency for practitioners to derive a practical way to calculate sample size for a three-arm equivalence trial. The primary endpoints of a clinical trial may not always be continuous, but may be discrete. In this paper, the authors derive power function and discuss sample size requirement for a three-arm equivalence trial with Poisson and negative binomial clinical endpoints. In addition, the authors examine the effect of the dispersion parameter on the power and the sample size by varying its coefficient from small to large. In extensive numerical studies, the authors demonstrate that required sample size heavily depends on the dispersion parameter. Therefore, misusing a Poisson model for negative binomial data may easily lose power up to 20%, depending on the value of the dispersion parameter.
Analysis of single-molecule fluorescence spectroscopic data with a Markov-modulated Poisson process.
Jäger, Mark; Kiel, Alexander; Herten, Dirk-Peter; Hamprecht, Fred A
2009-10-05
We present a photon-by-photon analysis framework for the evaluation of data from single-molecule fluorescence spectroscopy (SMFS) experiments using a Markov-modulated Poisson process (MMPP). A MMPP combines a discrete (and hidden) Markov process with an additional Poisson process reflecting the observation of individual photons. The algorithmic framework is used to automatically analyze the dynamics of the complex formation and dissociation of Cu2+ ions with the bidentate ligand 2,2'-bipyridine-4,4'dicarboxylic acid in aqueous media. The process of association and dissociation of Cu2+ ions is monitored with SMFS. The dcbpy-DNA conjugate can exist in two or more distinct states which influence the photon emission rates. The advantage of a photon-by-photon analysis is that no information is lost in preprocessing steps. Different model complexities are investigated in order to best describe the recorded data and to determine transition rates on a photon-by-photon basis. The main strength of the method is that it allows to detect intermittent phenomena which are masked by binning and that are difficult to find using correlation techniques when they are short-lived.
A Combined MPI-CUDA Parallel Solution of Linear and Nonlinear Poisson-Boltzmann Equation
Directory of Open Access Journals (Sweden)
José Colmenares
2014-01-01
Full Text Available The Poisson-Boltzmann equation models the electrostatic potential generated by fixed charges on a polarizable solute immersed in an ionic solution. This approach is often used in computational structural biology to estimate the electrostatic energetic component of the assembly of molecular biological systems. In the last decades, the amount of data concerning proteins and other biological macromolecules has remarkably increased. To fruitfully exploit these data, a huge computational power is needed as well as software tools capable of exploiting it. It is therefore necessary to move towards high performance computing and to develop proper parallel implementations of already existing and of novel algorithms. Nowadays, workstations can provide an amazing computational power: up to 10 TFLOPS on a single machine equipped with multiple CPUs and accelerators such as Intel Xeon Phi or GPU devices. The actual obstacle to the full exploitation of modern heterogeneous resources is efficient parallel coding and porting of software on such architectures. In this paper, we propose the implementation of a full Poisson-Boltzmann solver based on a finite-difference scheme using different and combined parallel schemes and in particular a mixed MPI-CUDA implementation. Results show great speedups when using the two schemes, achieving an 18.9x speedup using three GPUs.
Chen, Junning; Suenaga, Hanako; Hogg, Michael; Li, Wei; Swain, Michael; Li, Qing
2016-01-01
Despite their considerable importance to biomechanics, there are no existing methods available to directly measure apparent Poisson's ratio and friction coefficient of oral mucosa. This study aimed to develop an inverse procedure to determine these two biomechanical parameters by utilizing in vivo experiment of contact pressure between partial denture and beneath mucosa through nonlinear finite element (FE) analysis and surrogate response surface (RS) modelling technique. First, the in vivo denture-mucosa contact pressure was measured by a tactile electronic sensing sheet. Second, a 3D FE model was constructed based on the patient CT images. Third, a range of apparent Poisson's ratios and the coefficients of friction from literature was considered as the design variables in a series of FE runs for constructing a RS surrogate model. Finally, the discrepancy between computed in silico and measured in vivo results was minimized to identify the best matching Poisson's ratio and coefficient of friction. The established non-invasive methodology was demonstrated effective to identify such biomechanical parameters of oral mucosa and can be potentially used for determining the biomaterial properties of other soft biological tissues.
Energy Technology Data Exchange (ETDEWEB)
Wang, Z. [Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China); Institut für Materialphysik im Weltraum, Deutsches Zentrum für Luft- und Raumfahrt (DLR), 51170 Köln (Germany); Ngai, K. L., E-mail: ngai@df.unipi.it [CNR,-IPCF, Largo B. Pontecorvo 3, I-56127 Pisa (Italy); State Key Lab of Metastable Materials Science and Technology, Yanshan University, Qinhuangdao, Hebei 066004 (China); Wang, W. H. [Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China)
2015-07-21
In the paper K. L. Ngai et al., [J. Chem. 140, 044511 (2014)], the empirical correlation of ductility with the Poisson's ratio, ν{sub Poisson}, found in metallic glasses was theoretically explained by microscopic dynamic processes which link on the one hand ductility, and on the other hand the Poisson's ratio. Specifically, the dynamic processes are the primitive relaxation in the Coupling Model which is the precursor of the Johari–Goldstein β-relaxation, and the caged atoms dynamics characterized by the effective Debye–Waller factor f{sub 0} or equivalently the nearly constant loss (NCL) in susceptibility. All these processes and the parameters characterizing them are accessible experimentally except f{sub 0} or the NCL of caged atoms; thus, so far, the experimental verification of the explanation of the correlation between ductility and Poisson's ratio is incomplete. In the experimental part of this paper, we report dynamic mechanical measurement of the NCL of the metallic glass La{sub 60}Ni{sub 15}Al{sub 25} as-cast, and the changes by annealing at temperature below T{sub g}. The observed monotonic decrease of the NCL with aging time, reflecting the corresponding increase of f{sub 0}, correlates with the decrease of ν{sub Poisson}. This is important observation because such measurements, not made before, provide the missing link in confirming by experiment the explanation of the correlation of ductility with ν{sub Poisson}. On aging the metallic glass, also observed in the isochronal loss spectra is the shift of the β-relaxation to higher temperatures and reduction of the relaxation strength. These concomitant changes of the β-relaxation and NCL are the root cause of embrittlement by aging the metallic glass. The NCL of caged atoms is terminated by the onset of the primitive relaxation in the Coupling Model, which is generally supported by experiments. From this relation, the monotonic decrease of the NCL with aging time is caused by the
Site-Specific Study of In-Building Wireless Solutions with Poisson Traffic
DEFF Research Database (Denmark)
Liu, Zhen; Sørensen, Troels Bundgaard; Mogensen, Preben
2011-01-01
traffic model with fixed buffer size and Poisson arrival. Our new results show better performance for Femto cells with frequency reuse 1 at light to medium load, although the intelligent distributed system still obtains considerable better cell edge user throughput for the same number of access points....... system - together with another multi-cell system using our proposed centralized scheduling scheme. In our previous work, their performance is evaluated and compared in the LTE downlink context with full buffer traffic. Compared to real mobile networks, the full buffer traffic model is usually a worst......-case estimation of traffic load which causes severe interference conditions. Especially for Femto cells with universal frequency reuse it degrades system performance and may lead to biased conclusions on the relative performance of the different in-building solutions. In this study, we use a more realistic...
Wavelet-Based Poisson Solver for Use in Particle-in-Cell Simulations
Terzic, Balsa; Mihalcea, Daniel; Pogorelov, Ilya V
2005-01-01
We report on a successful implementation of a wavelet-based Poisson solver for use in 3D particle-in-cell simulations. One new aspect of our algorithm is its ability to treat the general (inhomogeneous) Dirichlet boundary conditions. The solver harnesses advantages afforded by the wavelet formulation, such as sparsity of operators and data sets, existence of effective preconditioners, and the ability simultaneously to remove numerical noise and further compress relevant data sets. Having tested our method as a stand-alone solver on two model problems, we merged it into IMPACT-T to obtain a fully functional serial PIC code. We present and discuss preliminary results of application of the new code to the modelling of the Fermilab/NICADD and AES/JLab photoinjectors.
Poisson and Porter-Thomas fluctuations in off-yrast rotational transitions
International Nuclear Information System (INIS)
Matsuo, M.; Doessing, T.; Herskind, B.; Frauendorf, S.
1993-01-01
Fluctuations associated with stretched E2 transitions from high-spin levels in nuclei around 168 Yb are investigated by a cranked shell model extended to include residual two-body interactions. In the cranked mean-field model without residual interactions, it is found that gamma-ray energies behave like random variables and the energy spectra show Poisson fluctuation. With two-body residual interactions included, the discrete transition pattern with unmixed rotational bands is still valid up to around 600 keV above yrast, in good agreement with experiments. At higher excitation energy, a gradual onset of rotational damping emerges. At 1.8 MeV above yrast, complete damping is observed with GOE-type fluctuations for both energy levels and transition strengths (Porter-Thomas fluctuations). (orig.)
An alternating minimization method for blind deconvolution from Poisson data
International Nuclear Information System (INIS)
Prato, Marco; La Camera, Andrea; Bonettini, Silvia
2014-01-01
Blind deconvolution is a particularly challenging inverse problem since information on both the desired target and the acquisition system have to be inferred from the measured data. When the collected data are affected by Poisson noise, this problem is typically addressed by the minimization of the Kullback-Leibler divergence, in which the unknowns are sought in particular feasible sets depending on the a priori information provided by the specific application. If these sets are separated, then the resulting constrained minimization problem can be addressed with an inexact alternating strategy. In this paper we apply this optimization tool to the problem of reconstructing astronomical images from adaptive optics systems, and we show that the proposed approach succeeds in providing very good results in the blind deconvolution of nondense stellar clusters
Beatification: Flattening Poisson brackets for plasma theory and computation
Morrison, P. J.; Viscondi, T. F.; Caldas, I.
2017-10-01
A perturbative method called beatification is presented for producing nonlinear Hamiltonian fluid and plasma theories. Plasma Hamiltonian theories, fluid and kinetic, are naturally described in terms of noncanonical variables. The beatification procedure amounts to finding a transformation that removes the explicit variable dependence from a noncanonical Poisson bracket and replaces it with a fixed dependence on a chosen state in the phase space. As such, beatification is a major step toward casting the Hamiltonian system in its canonical form, thus enabling or facilitating the use of analytical and numerical techniques that require or favor a representation in terms of canonical, or beatified, Hamiltonian variables. Examples will be given. U.S. D.O.E No. #DE-FG02-04ER-54742.
Particular solutions of generalized Euler-Poisson-Darboux equation
Directory of Open Access Journals (Sweden)
Rakhila B. Seilkhanova
2015-01-01
Full Text Available In this article we consider the generalized Euler-Poisson-Darboux equation $$ {u}_{tt}+\\frac{2\\gamma }{t}{{u}_{t}}={u}_{xx}+{u}_{yy} +\\frac{2\\alpha }{x}{{u}_{x}}+\\frac{2\\beta }{y}{{u}_y},\\quad x>0,\\;y>0,\\;t>0. $$ We construct particular solutions in an explicit form expressed by the Lauricella hypergeometric function of three variables. Properties of each constructed solutions have been investigated in sections of surfaces of the characteristic cone. Precisely, we prove that found solutions have singularity $1/r$ at $r\\to 0$, where ${{r}^2}={{( x-{{x}_0}}^2}+{{( y-{{y}_0}}^2}-{{( t-{{t}_0}}^2}$.
On the FACR( l) algorithm for the discrete Poisson equation
Temperton, Clive
1980-03-01
Direct methods for the solution of the discrete Poisson equation over a rectangle are commonly based either on Fourier transforms or on block-cyclic reduction. The relationship between these two approaches is demonstrated explicitly, and used to derive the FACR( l) algorithm in which the Fourier transform approach is combined with l preliminary steps of cyclic reduction. It is shown that the optimum choice of l leads to an algorithm for which the operation count per mesh point is almost independent of the mesh size. Numerical results concerning timing and round-off error are presented for the N × N Dirichlet problem for various values of N and l. Extensions to more general problems, and to implementation on parallel or vector computers are briefly discussed.
Recent advances in the Poisson/superfish codes
International Nuclear Information System (INIS)
Ryne, R.; Barts, T.; Chan, K.C.D.; Cooper, R.; Deaven, H.; Merson, J.; Rodenz, G.
1992-01-01
We report on advances in the POISSON/SUPERFISH family of codes used in the design and analysis of magnets and rf cavities. The codes include preprocessors for mesh generation and postprocessors for graphical display of output and calculation of auxiliary quantities. Release 3 became available in January 1992; it contains many code corrections and physics enhancements, and it also includes support for PostScript, DISSPLA, GKS and PLOT10 graphical output. Release 4 will be available in September 1992; it is free of all bit packing, making the codes more portable and able to treat very large numbers of mesh points. Release 4 includes the preprocessor FRONT and a new menu-driven graphical postprocessor that runs on workstations under X-Windows and that is capable of producing arrow plots. We will present examples that illustrate the new capabilities of the codes. (author). 6 refs., 3 figs
Tetrahedral meshing via maximal Poisson-disk sampling
Guo, Jianwei
2016-02-15
In this paper, we propose a simple yet effective method to generate 3D-conforming tetrahedral meshes from closed 2-manifold surfaces. Our approach is inspired by recent work on maximal Poisson-disk sampling (MPS), which can generate well-distributed point sets in arbitrary domains. We first perform MPS on the boundary of the input domain, we then sample the interior of the domain, and we finally extract the tetrahedral mesh from the samples by using 3D Delaunay or regular triangulation for uniform or adaptive sampling, respectively. We also propose an efficient optimization strategy to protect the domain boundaries and to remove slivers to improve the meshing quality. We present various experimental results to illustrate the efficiency and the robustness of our proposed approach. We demonstrate that the performance and quality (e.g., minimal dihedral angle) of our approach are superior to current state-of-the-art optimization-based approaches.
Cryoconservation du sperme et des embryons de poissons
Maisse, Gérard; Labbé, Catherine; Ogier de Baulny, Bénédicte; Leveroni Calvi, Sylvia; Haffray, Pierrick
1998-01-01
Le développement des programmes de sélection génétique en pisciculture et la protection de la biodiversité de l’ichtyofaune sauvage justifient la création de cryo-banques de sperme et d’embryons de poissons. Les travaux sur la formulation des dilueurs de congélation montrent que l’on doit tenir compte à la fois de l’espèce cible, du type cellulaire concerné et des interactions entre les différents composants du dilueur. L’aptitude à la cryoconservation du sperme est très variable suivant les ...
Bases chimiosensorielles du comportement alimentaire chez les poissons
Saglio, P.
1981-01-01
Le comportement alimentaire, indispensable à la survie de l'individu et donc de l'espèce, occupe à ce titre une position de première importance dans la hiérarchie des comportements fondamentaux qui tous en dépendent très étroitement. Chez les poissons, cette prééminence se trouve illustrée par l'extrême diversité des supports sensoriels impliqués et des expressions comportementales qui leur sont liées. A la suite d'un certain nombre de mises en évidence neurophysiologiques et éthologiques de ...
Ingels, Frank; Owens, John; Daniel, Steven
1989-01-01
The protocol definition and terminal hardware for the modified free access protocol, a communications protocol similar to Ethernet, are developed. A MFA protocol simulator and a CSMA/CD math model are also developed. The protocol is tailored to communication systems where the total traffic may be divided into scheduled traffic and Poisson traffic. The scheduled traffic should occur on a periodic basis but may occur after a given event such as a request for data from a large number of stations. The Poisson traffic will include alarms and other random traffic. The purpose of the protocol is to guarantee that scheduled packets will be delivered without collision. This is required in many control and data collection systems. The protocol uses standard Ethernet hardware and software requiring minimum modifications to an existing system. The modification to the protocol only affects the Ethernet transmission privileges and does not effect the Ethernet receiver.
Egan, Raphael; Gibou, Frédéric
2017-10-01
We present a discretization method for the multidimensional Dirac distribution. We show its applicability in the context of integration problems, and for discretizing Dirac-distributed source terms in Poisson equations with constant or variable diffusion coefficients. The discretization is cell-based and can thus be applied in a straightforward fashion to Quadtree/Octree grids. The method produces second-order accurate results for integration. Superlinear convergence is observed when it is used to model Dirac-distributed source terms in Poisson equations: the observed order of convergence is 2 or slightly smaller. The method is consistent with the discretization of Dirac delta distribution for codimension one surfaces presented in [1,2]. We present Quadtree/Octree construction procedures to preserve convergence and present various numerical examples, including multi-scale problems that are intractable with uniform grids.
A geometric multigrid Poisson solver for domains containing solid inclusions
Botto, Lorenzo
2013-03-01
A Cartesian grid method for the fast solution of the Poisson equation in three-dimensional domains with embedded solid inclusions is presented and its performance analyzed. The efficiency of the method, which assume Neumann conditions at the immersed boundaries, is comparable to that of a multigrid method for regular domains. The method is light in terms of memory usage, and easily adaptable to parallel architectures. Tests with random and ordered arrays of solid inclusions, including spheres and ellipsoids, demonstrate smooth convergence of the residual for small separation between the inclusion surfaces. This feature is important, for instance, in simulations of nearly-touching finite-size particles. The implementation of the method, “MG-Inc”, is available online. Catalogue identifier: AEOE_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOE_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 19068 No. of bytes in distributed program, including test data, etc.: 215118 Distribution format: tar.gz Programming language: C++ (fully tested with GNU GCC compiler). Computer: Any machine supporting standard C++ compiler. Operating system: Any OS supporting standard C++ compiler. RAM: About 150MB for 1283 resolution Classification: 4.3. Nature of problem: Poisson equation in domains containing inclusions; Neumann boundary conditions at immersed boundaries. Solution method: Geometric multigrid with finite-volume discretization. Restrictions: Stair-case representation of the immersed boundaries. Running time: Typically a fraction of a minute for 1283 resolution.
A multiresolution method for solving the Poisson equation using high order regularization
DEFF Research Database (Denmark)
Hejlesen, Mads Mølholm; Walther, Jens Honore
2016-01-01
and regularized Green's functions corresponding to the difference in the spatial resolution between the patches. The full solution is obtained utilizing the linearity of the Poisson equation enabling super-position of solutions. We show that the multiresolution Poisson solver produces convergence rates......We present a novel high order multiresolution Poisson solver based on regularized Green's function solutions to obtain exact free-space boundary conditions while using fast Fourier transforms for computational efficiency. Multiresolution is a achieved through local refinement patches...
Berti, Claudio; Gillespie, Dirk; Bardhan, Jaydeep P.; Eisenberg, Robert S.; Fiegna, Claudio
2012-07-01
Particle-based simulation represents a powerful approach to modeling physical systems in electronics, molecular biology, and chemical physics. Accounting for the interactions occurring among charged particles requires an accurate and efficient solution of Poisson's equation. For a system of discrete charges with inhomogeneous dielectrics, i.e., a system with discontinuities in the permittivity, the boundary element method (BEM) is frequently adopted. It provides the solution of Poisson's equation, accounting for polarization effects due to the discontinuity in the permittivity by computing the induced charges at the dielectric boundaries. In this framework, the total electrostatic potential is then found by superimposing the elemental contributions from both source and induced charges. In this paper, we present a comparison between two BEMs to solve a boundary-integral formulation of Poisson's equation, with emphasis on the BEMs' suitability for particle-based simulations in terms of solution accuracy and computation speed. The two approaches are the collocation and qualocation methods. Collocation is implemented following the induced-charge computation method of D. Boda [J. Chem. Phys.JCPSA60021-960610.1063/1.2212423 125, 034901 (2006)]. The qualocation method is described by J. Tausch [IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsITCSDI0278-007010.1109/43.969433 20, 1398 (2001)]. These approaches are studied using both flat and curved surface elements to discretize the dielectric boundary, using two challenging test cases: a dielectric sphere embedded in a different dielectric medium and a toy model of an ion channel. Earlier comparisons of the two BEM approaches did not address curved surface elements or semiatomistic models of ion channels. Our results support the earlier findings that for flat-element calculations, qualocation is always significantly more accurate than collocation. On the other hand, when the dielectric boundary
Berti, Claudio; Gillespie, Dirk; Bardhan, Jaydeep P; Eisenberg, Robert S; Fiegna, Claudio
2012-07-01
Particle-based simulation represents a powerful approach to modeling physical systems in electronics, molecular biology, and chemical physics. Accounting for the interactions occurring among charged particles requires an accurate and efficient solution of Poisson's equation. For a system of discrete charges with inhomogeneous dielectrics, i.e., a system with discontinuities in the permittivity, the boundary element method (BEM) is frequently adopted. It provides the solution of Poisson's equation, accounting for polarization effects due to the discontinuity in the permittivity by computing the induced charges at the dielectric boundaries. In this framework, the total electrostatic potential is then found by superimposing the elemental contributions from both source and induced charges. In this paper, we present a comparison between two BEMs to solve a boundary-integral formulation of Poisson's equation, with emphasis on the BEMs' suitability for particle-based simulations in terms of solution accuracy and computation speed. The two approaches are the collocation and qualocation methods. Collocation is implemented following the induced-charge computation method of D. Boda et al. [J. Chem. Phys. 125, 034901 (2006)]. The qualocation method is described by J. Tausch et al. [IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 20, 1398 (2001)]. These approaches are studied using both flat and curved surface elements to discretize the dielectric boundary, using two challenging test cases: a dielectric sphere embedded in a different dielectric medium and a toy model of an ion channel. Earlier comparisons of the two BEM approaches did not address curved surface elements or semiatomistic models of ion channels. Our results support the earlier findings that for flat-element calculations, qualocation is always significantly more accurate than collocation. On the other hand, when the dielectric boundary is discretized with curved surface elements, the
DEFF Research Database (Denmark)
Sibani, Paolo
2007-01-01
in a correlated fashion and through irreversible bursts, `quakes', which punctuate reversible and equilibrium-like fluctuations of zero average. The temporal distribution of the quakes is a Poisson distribution with an average growing logarithmically on time, indicating that the quakes are triggered by record...... to capture the time dependencies of the EA simulation results. Finally, we argue that whenever the changes of the linear response function and of its conjugate autocorrelation function follow from the same intermittent events a fluctuation-dissipation-like relation can arise between the two in off......We study the intermittent behavior of the energy decay and the linear magnetic response of a glassy system during isothermal aging after a deep thermal quench, using the Edward-Anderson spin glass model as a paradigmatic example. The large intermittent changes in the two observables occur...
Compound Poisson Processes and Clustered Damage of Radiation Induced DNA Double Strand Breaks
International Nuclear Information System (INIS)
Gudowska-Nowak, E.; Ritter, S.; Taucher-Scholz, G.; Kraft, G.
2000-01-01
Recent experimental data have demonstrated that DNA damage induced by densely ionizing radiation in mammalian cells is distributed along the DNA molecule in the form of clusters. The principal constituent of DNA damage are double-strand breaks (DSB) which are formed when the breaks occur in both DNA strands and are directly opposite or separated by only a few base pairs. DSBs are believed to be most important lesions produced in chromosomes by radiation; interaction between DSBs can lead to cell killing, mutation or carcinogenesis. The paper discusses a model of clustered DSB formation viewed in terms of compound Poisson process along with the predictive essay of the formalism in application to experimental data. (author)
FOOD INSECURITY AND EDUCATIONAL ACHIEVEMENT: A MULTI-LEVEL GENERALIZATION OF POISSON REGRESSION
Directory of Open Access Journals (Sweden)
Allison Jennifer Ames
2016-01-01
Full Text Available This research examined the relationship between food insecurity, the National School Lunch Program (NSLP, and academic achievement in Georgia’s public school system. Georgia is located in the southern U.S. states, where food insecurity has been particularly prevalent. A multilevel Poisson generalized linear model was used to examine the relationship between food insecurity and academic achievement. Findings confirm a strong inverse relationship between food insecurity, as exhibited by participation in the National School Lunch Program, and academic achievement for elementary-age children. The strength of the relationship between food insecurity and academic achievement was different for the younger, elementary-age students (fifth grade than for the older, middle school-age (eighth grade students, a key distinction between this study and other research.
Analytic Bayesian solution of the two-stage poisson-type problem in probabilistic risk analysis
International Nuclear Information System (INIS)
Frohner, F.H.
1985-01-01
The basic purpose of probabilistic risk analysis is to make inferences about the probabilities of various postulated events, with an account of all relevant information such as prior knowledge and operating experience with the specific system under study, as well as experience with other similar systems. Estimation of the failure rate of a Poisson-type system leads to an especially simple Bayesian solution in closed form if the prior probabilty implied by the invariance properties of the problem is properly taken into account. This basic simplicity persists if a more realistic prior, representing order of magnitude knowledge of the rate parameter, is employed instead. Moreover, the more realistic prior allows direct incorporation of experience gained from other similar systems, without need to postulate a statistical model for an underlying ensemble. The analytic formalism is applied to actual nuclear reactor data
Evaluation of ion binding to DNA duplexes using a size-modified Poisson-Boltzmann theory.
Chu, Vincent B; Bai, Yu; Lipfert, Jan; Herschlag, Daniel; Doniach, Sebastian
2007-11-01
Poisson-Boltzmann (PB) theory is among the most widely applied electrostatic theories in biological and chemical science. Despite its reasonable success in explaining a wide variety of phenomena, it fails to incorporate two basic physical effects, ion size and ion-ion correlations, into its theoretical treatment. Recent experimental work has shown significant deviations from PB theory in competitive monovalent and divalent ion binding to a DNA duplex. The experimental data for monovalent binding are consistent with a hypothesis that attributes these deviations to counterion size. To model the observed differences, we have generalized an existing size-modified Poisson-Boltzmann (SMPB) theory and developed a new numerical implementation that solves the generalized theory around complex, atomistic representations of biological molecules. The results of our analysis show that good agreement to data at monovalent ion concentrations up to approximately 150 mM can be attained by adjusting the ion-size parameters in the new size-modified theory. SMPB calculations employing calibrated ion-size parameters predict experimental observations for other nucleic acid structures and salt conditions, demonstrating that the theory is predictive. We are, however, unable to model the observed deviations in the divalent competition data with a theory that only accounts for size but neglects ion-ion correlations, highlighting the need for theoretical descriptions that further incorporate ion-ion correlations. The accompanying numerical solver has been released publicly, providing the general scientific community the ability to compute SMPB solutions around a variety of different biological structures with only modest computational resources.
International Nuclear Information System (INIS)
Er-Qin, Wang; Fu-Hu, Liu; Jian-Xin, Sun; Rahim, Magda A.; Fakhraddin, S.
2011-01-01
The multiplicity distributions of projectile fragments emitted in interactions of different nuclei with emulsion are studied by using a multi-source model. Our calculated results show that the projectile fragments can be described by the model and each source contributes an exponential distribution. As the weighted sum of the folding result of many exponential distributions, a multi-component Erlang distribution is used to describe the experimental data. The relationship between the height (or width) of the distribution and the mass of the incident projectile, as well as the dependence of projectile fragments on target groups, are investigated too. (nuclear physics)
Dynamic Response of Non-Linear Inelsatic Systems to Poisson-Driven Stochastic Excitations
DEFF Research Database (Denmark)
Nielsen, Søren R. K.; Iwankiewicz, R.
A single-degree-of-freedom inelastic system subject to a stochastic excitation in form of a Poisson-distributed train of impulses is considered. The state variables of the system form a non-diffusive, Poisson-driven Markov process. Two approximate analytical techniques are developed: modification...
A relation between Liapunov stability, non-wanderingness and Poisson stability
International Nuclear Information System (INIS)
Ahmad, K.H.
1985-07-01
In this work, some of the relations among Liapunov stability, non-wanderingness and Poisson stability are considered. In particular it is shown that for a non-wandering point in a set, positive (resp. negative) Liapunov stability in that set implies positive (resp. negative) Poisson stability in the same set. (author)
Approximation by some combinations of Poisson integrals for Hermite and Laguerre expansions
Directory of Open Access Journals (Sweden)
Grażyna Krech
2013-02-01
Full Text Available The aim of this paper is the study of a rate of convergence of some combinations of Poisson integrals for Hermite and Laguerre expansions. We are able to achieve faster convergence for our modified operators over the Poisson integrals. We prove also the Voronovskaya type theorem for these new operators.
Confidence limits for parameters of Poisson and binomial distributions
International Nuclear Information System (INIS)
Arnett, L.M.
1976-04-01
The confidence limits for the frequency in a Poisson process and for the proportion of successes in a binomial process were calculated and tabulated for the situations in which the observed values of the frequency or proportion and an a priori distribution of these parameters are available. Methods are used that produce limits with exactly the stated confidence levels. The confidence interval [a,b] is calculated so that Pr [a less than or equal to lambda less than or equal to b c,μ], where c is the observed value of the parameter, and μ is the a priori hypothesis of the distribution of this parameter. A Bayesian type analysis is used. The intervals calculated are narrower and appreciably different from results, known to be conservative, that are often used in problems of this type. Pearson and Hartley recognized the characteristics of their methods and contemplated that exact methods could someday be used. The calculation of the exact intervals requires involved numerical analyses readily implemented only on digital computers not available to Pearson and Hartley. A Monte Carlo experiment was conducted to verify a selected interval from those calculated. This numerical experiment confirmed the results of the analytical methods and the prediction of Pearson and Hartley that their published tables give conservative results
METHOD OF FOREST FIRES PROBABILITY ASSESSMENT WITH POISSON LAW
Directory of Open Access Journals (Sweden)
A. S. Plotnikova
2016-01-01
Full Text Available The article describes the method for the forest fire burn probability estimation on a base of Poisson distribution. The λ parameter is assumed to be a mean daily number of fires detected for each Forest Fire Danger Index class within specific period of time. Thus, λ was calculated for spring, summer and autumn seasons separately. Multi-annual daily Forest Fire Danger Index values together with EO-derived hot spot map were input data for the statistical analysis. The major result of the study is generation of the database on forest fire burn probability. Results were validated against EO daily data on forest fires detected over Irkutsk oblast in 2013. Daily weighted average probability was shown to be linked with the daily number of detected forest fires. Meanwhile, there was found a number of fires which were developed when estimated probability was low. The possible explanation of this phenomenon was provided.
POISSON project. III. Investigating the evolution of the mass accretion rate
Antoniucci, S.; García López, R.; Nisini, B.; Caratti o Garatti, A.; Giannini, T.; Lorenzetti, D.
2014-12-01
Context. As part of the Protostellar Optical-Infrared Spectral Survey On NTT (POISSON) project, we present the results of the analysis of low-resolution near-IR spectroscopic data (0.9-2.4 μm) of two samples of young stellar objects in the Lupus (52 objects) and Serpens (17 objects) star-forming clouds, with masses in the range of 0.1 to 2.0 M⊙ and ages spanning from 105 to a few 107 yr. Aims: After determining the accretion parameters of the targets by analysing their H i near-IR emission features, we added the results from the Lupus and Serpens clouds to those from previous regions (investigated in POISSON with the same methodology) to obtain a final catalogue (143 objects) of mass accretion rate values (Ṁacc) derived in a homogeneous and consistent fashion. Our final goal is to analyse how Ṁacc correlates with the stellar mass (M∗) and how it evolves in time in the whole POISSON sample. Methods: We derived the accretion luminosity (Lacc) and Ṁacc for Lupus and Serpens objects from the Brγ (Paβ in a few cases) line by using relevant empirical relationships available in the literature that connect the H i line luminosity and Lacc. To minimise the biases that arise from adopting literature data that are based on different evolutionary models and also for self-consistency, we re-derived mass and age for each source of the POISSON samples using the same set of evolutionary tracks. Results: We observe a correlation Ṁacc~M*2.2 between mass accretion rate and stellar mass, similarly to what has previously been observed in several star-forming regions. We find that the time variation of Ṁacc is roughly consistent with the expected evolution of the accretion rate in viscous disks, with an asymptotic decay that behaves as t-1.6. However, Ṁacc values are characterised by a large scatter at similar ages and are on average higher than the predictions of viscous models. Conclusions: Although part of the scattering may be related to systematics due to the
Directory of Open Access Journals (Sweden)
An Pan
2014-01-01
Full Text Available Addressing the problems of a health care center which produces tailor-made clothes for specific people, the paper proposes a single product continuous review model and establishes an optimal policy for the center based on (Q,r control policy to minimize expected average cost on an order cycle. A generic mathematical model to compute cost on real-time inventory level is developed to generate optimal order quantity under stochastic stock variation. The customer demands are described as compound Poisson process. Comparisons on cost between optimization method and experience-based decision on Q are made through numerical studies conducted for the inventory system of the center.
On-the-fly Numerical Surface Integration for Finite-Difference Poisson-Boltzmann Methods.
Cai, Qin; Ye, Xiang; Wang, Jun; Luo, Ray
2011-11-01
Most implicit solvation models require the definition of a molecular surface as the interface that separates the solute in atomic detail from the solvent approximated as a continuous medium. Commonly used surface definitions include the solvent accessible surface (SAS), the solvent excluded surface (SES), and the van der Waals surface. In this study, we present an efficient numerical algorithm to compute the SES and SAS areas to facilitate the applications of finite-difference Poisson-Boltzmann methods in biomolecular simulations. Different from previous numerical approaches, our algorithm is physics-inspired and intimately coupled to the finite-difference Poisson-Boltzmann methods to fully take advantage of its existing data structures. Our analysis shows that the algorithm can achieve very good agreement with the analytical method in the calculation of the SES and SAS areas. Specifically, in our comprehensive test of 1,555 molecules, the average unsigned relative error is 0.27% in the SES area calculations and 1.05% in the SAS area calculations at the grid spacing of 1/2Å. In addition, a systematic correction analysis can be used to improve the accuracy for the coarse-grid SES area calculations, with the average unsigned relative error in the SES areas reduced to 0.13%. These validation studies indicate that the proposed algorithm can be applied to biomolecules over a broad range of sizes and structures. Finally, the numerical algorithm can also be adapted to evaluate the surface integral of either a vector field or a scalar field defined on the molecular surface for additional solvation energetics and force calculations.
Incompressible SPH (ISPH) with fast Poisson solver on a GPU
Chow, Alex D.; Rogers, Benedict D.; Lind, Steven J.; Stansby, Peter K.
2018-05-01
This paper presents a fast incompressible SPH (ISPH) solver implemented to run entirely on a graphics processing unit (GPU) capable of simulating several millions of particles in three dimensions on a single GPU. The ISPH algorithm is implemented by converting the highly optimised open-source weakly-compressible SPH (WCSPH) code DualSPHysics to run ISPH on the GPU, combining it with the open-source linear algebra library ViennaCL for fast solutions of the pressure Poisson equation (PPE). Several challenges are addressed with this research: constructing a PPE matrix every timestep on the GPU for moving particles, optimising the limited GPU memory, and exploiting fast matrix solvers. The ISPH pressure projection algorithm is implemented as 4 separate stages, each with a particle sweep, including an algorithm for the population of the PPE matrix suitable for the GPU, and mixed precision storage methods. An accurate and robust ISPH boundary condition ideal for parallel processing is also established by adapting an existing WCSPH boundary condition for ISPH. A variety of validation cases are presented: an impulsively started plate, incompressible flow around a moving square in a box, and dambreaks (2-D and 3-D) which demonstrate the accuracy, flexibility, and speed of the methodology. Fragmentation of the free surface is shown to influence the performance of matrix preconditioners and therefore the PPE matrix solution time. The Jacobi preconditioner demonstrates robustness and reliability in the presence of fragmented flows. For a dambreak simulation, GPU speed ups demonstrate up to 10-18 times and 1.1-4.5 times compared to single-threaded and 16-threaded CPU run times respectively.
Martina, R; Kay, R; van Maanen, R; Ridder, A
2015-01-01
Clinical studies in overactive bladder have traditionally used analysis of covariance or nonparametric methods to analyse the number of incontinence episodes and other count data. It is known that if the underlying distributional assumptions of a particular parametric method do not hold, an alternative parametric method may be more efficient than a nonparametric one, which makes no assumptions regarding the underlying distribution of the data. Therefore, there are advantages in using methods based on the Poisson distribution or extensions of that method, which incorporate specific features that provide a modelling framework for count data. One challenge with count data is overdispersion, but methods are available that can account for this through the introduction of random effect terms in the modelling, and it is this modelling framework that leads to the negative binomial distribution. These models can also provide clinicians with a clearer and more appropriate interpretation of treatment effects in terms of rate ratios. In this paper, the previously used parametric and non-parametric approaches are contrasted with those based on Poisson regression and various extensions in trials evaluating solifenacin and mirabegron in patients with overactive bladder. In these applications, negative binomial models are seen to fit the data well. Copyright © 2014 John Wiley & Sons, Ltd.
Control Multivariante Estadístico de Variables Discretas tipo Poisson
GARCIA BUSTOS, SANDRA LORENA
2016-01-01
En algunos casos, cuando el número de defectos de un proceso de producción tiene que ser controlada, la distribución de Poisson se emplea para modelar la frecuencia de estos defectos y para desarrollar un gráfico de control. En este trabajo se analiza el control de características de calidad p> 1 de Poisson . Cuando este control se necesita, hay dos enfoques principales: 1 - Un gráfico para cada variable de Poisson, el esquema múltiple.. 2 -. Sólo una gráfico para todas las variables, el sist...
Hamiltonian field description of the one-dimensional Poisson-Vlasov equations
International Nuclear Information System (INIS)
Morrison, P.J.
1981-07-01
The one-dimensional Poisson-Vlasov equations are cast into Hamiltonian form. A Poisson Bracket in terms of the phase space density, as sole dynamical variable, is presented. This Poisson bracket is not of the usual form, but possesses the commutator properties of antisymmetry, bilinearity, and nonassociativity by virtue of the Jacobi requirement. Clebsch potentials are seen to yield a conventional (canonical) formulation. This formulation is discretized by expansion in terms of an arbitrary complete set of basis functions. In particular, a wave field representation is obtained
A regularization method for solving the Poisson equation for mixed unbounded-periodic domains
DEFF Research Database (Denmark)
Spietz, Henrik Juul; Mølholm Hejlesen, Mads; Walther, Jens Honoré
2018-01-01
the regularized unbounded-periodic Green's functions can be implemented in an FFT-based Poisson solver to obtain a convergence rate corresponding to the regularization order of the Green's function. The high order is achieved without any additional computational cost from the conventional FFT-based Poisson solver...... and enables the calculation of the derivative of the solution to the same high order by direct spectral differentiation. We illustrate an application of the FFT-based Poisson solver by using it with a vortex particle mesh method for the approximation of incompressible flow for a problem with a single periodic...
DEFF Research Database (Denmark)
Harrod, Steven; Kelton, W. David
2006-01-01
with piecewise-constant instantaneous rate functions, a capability that has been implemented in commercial simulation software. They test these algorithms in C programs and make comparisons of accuracy, speed, and variability across disparate rate functions and microprocessor architectures. Choice of optimal......Nonstationary Poisson processes are appropriate in many applications, including disease studies, transportation, finance, and social policy. The authors review the risks of ignoring nonstationarity in Poisson processes and demonstrate three algorithms for generation of Poisson processes...... algorithm could not be predicted without knowledge of microprocessor architecture....
Zaitsev, Vladimir Y.; Radostin, Andrey V.; Dyskin, Arcady V.; Pasternak, Elena
2017-04-01
We report results of analysis of literature data on P- and S-wave velocities of rocks subjected to variable hydrostatic pressure. Out of about 90 examined samples, in more than 40% of the samples the reconstructed Poisson's ratios are negative for lowest confining pressure with gradual transition to the conventional positive values at higher pressure. The portion of rocks exhibiting negative Poisson's ratio appeared to be unexpectedly high. To understand the mechanism of negative Poisson's ratio, pressure dependences of P- and S-wave velocities were analyzed using the effective medium model in which the reduction in the elastic moduli due to cracks is described in terms of compliances with respect to shear and normal loading that are imparted to the rock by the presence of cracks. This is in contrast to widely used descriptions of effective cracked medium based on a specific crack model (e.g., penny-shape crack) in which the ratio between normal and shear compliances of such a crack is strictly predetermined. The analysis of pressure-dependences of the elastic wave velocities makes it possible to reveal the ratio between pure normal and shear compliances (called q-ratio below) for real defects and quantify their integral content in the rock. The examination performed demonstrates that a significant portion (over 50%) of cracks exhibit q-ratio several times higher than that assumed for the conventional penny-shape cracks. This leads to faster reduction of the Poisson's ratio with increasing the crack concentration. Samples with negative Poisson's ratio are characterized by elevated q-ratio and simultaneously crack concentration. Our results clearly indicate that the traditional crack model is not adequate for a significant portion of rocks and that the interaction between the opposite crack faces leading to domination of the normal compliance and reduced shear displacement discontinuity can play an important role in the mechanical behavior of rocks.
Liu, J. J. F.; Fitzpatrick, P. M.
1975-01-01
A mathematical model is developed for studying the effects of gravity gradient torque on the attitude stability of a tumbling triaxial rigid satellite. Poisson equations are used to investigate the rotation of the satellite (which is in elliptical orbit about an attracting point mass) about its center of mass. An averaging method is employed to obtain an intermediate set of differential equations for the nonresonant, secular behavior of the osculating elements which describe the rotational motions of the satellite, and the averaged equations are then integrated to obtain long-term secular solutions for the osculating elements.
Poisson cluster analysis of cardiac arrest incidence in Columbus, Ohio.
Warden, Craig; Cudnik, Michael T; Sasson, Comilla; Schwartz, Greg; Semple, Hugh
2012-01-01
Scarce resources in disease prevention and emergency medical services (EMS) need to be focused on high-risk areas of out-of-hospital cardiac arrest (OHCA). Cluster analysis using geographic information systems (GISs) was used to find these high-risk areas and test potential predictive variables. This was a retrospective cohort analysis of EMS-treated adults with OHCAs occurring in Columbus, Ohio, from April 1, 2004, through March 31, 2009. The OHCAs were aggregated to census tracts and incidence rates were calculated based on their adult populations. Poisson cluster analysis determined significant clusters of high-risk census tracts. Both census tract-level and case-level characteristics were tested for association with high-risk areas by multivariate logistic regression. A total of 2,037 eligible OHCAs occurred within the city limits during the study period. The mean incidence rate was 0.85 OHCAs/1,000 population/year. There were five significant geographic clusters with 76 high-risk census tracts out of the total of 245 census tracts. In the case-level analysis, being in a high-risk cluster was associated with a slightly younger age (-3 years, adjusted odds ratio [OR] 0.99, 95% confidence interval [CI] 0.99-1.00), not being white, non-Hispanic (OR 0.54, 95% CI 0.45-0.64), cardiac arrest occurring at home (OR 1.53, 95% CI 1.23-1.71), and not receiving bystander cardiopulmonary resuscitation (CPR) (OR 0.77, 95% CI 0.62-0.96), but with higher survival to hospital discharge (OR 1.78, 95% CI 1.30-2.46). In the census tract-level analysis, high-risk census tracts were also associated with a slightly lower average age (-0.1 years, OR 1.14, 95% CI 1.06-1.22) and a lower proportion of white, non-Hispanic patients (-0.298, OR 0.04, 95% CI 0.01-0.19), but also a lower proportion of high-school graduates (-0.184, OR 0.00, 95% CI 0.00-0.00). This analysis identified high-risk census tracts and associated census tract-level and case-level characteristics that can be used to
A Hands-on Activity for Teaching the Poisson Distribution Using the Stock Market
Dunlap, Mickey; Studstill, Sharyn
2014-01-01
The number of increases a particular stock makes over a fixed period follows a Poisson distribution. This article discusses using this easily-found data as an opportunity to let students become involved in the data collection and analysis process.
Hung, Tran Loc; Giang, Le Truong
2016-01-01
Using the Stein-Chen method some upper bounds in Poisson approximation for distributions of row-wise triangular arrays of independent negative-binomial distributed random variables are established in this note.
Equal-Time and Equal-Space Poisson Brackets of the N -Component Coupled NLS Equation
International Nuclear Information System (INIS)
Zhou Ru-Guang; Li Pei-Yao; Gao Yuan
2017-01-01
Two Poisson brackets for the N-component coupled nonlinear Schrödinger (NLS) equation are derived by using the variantional principle. The first one is called the equal-time Poisson bracket which does not depend on time but only on the space variable. Actually it is just the usual one describing the time evolution of system in the traditional theory of integrable Hamiltonian systems. The second one is equal-space and new. It is shown that the spatial part of Lax pair with respect to the equal-time Poisson bracket and temporal part of Lax pair with respect to the equal-space Poisson bracket share the same r-matrix formulation. These properties are similar to that of the NLS equation. (paper)
2010-11-01
The resilient modulus and Poissons ratio of base and sublayers in highway use are : important parameters in design and quality control process. The currently used techniques : include CBR (California Bearing Ratio) test, resilient modulus test,...
International Nuclear Information System (INIS)
Grigoriu, Mircea; Samorodnitsky, Gennady
2004-01-01
Two methods are considered for assessing the asymptotic stability of the trivial solution of linear stochastic differential equations driven by Poisson white noise, interpreted as the formal derivative of a compound Poisson process. The first method attempts to extend a result for diffusion processes satisfying linear stochastic differential equations to the case of linear equations with Poisson white noise. The developments for the method are based on Ito's formula for semimartingales and Lyapunov exponents. The second method is based on a geometric ergodic theorem for Markov chains providing a criterion for the asymptotic stability of the solution of linear stochastic differential equations with Poisson white noise. Two examples are presented to illustrate the use and evaluate the potential of the two methods. The examples demonstrate limitations of the first method and the generality of the second method
Solution of the Kolmogorov-Nikol'skii problem for the Poisson integrals of continuous functions
International Nuclear Information System (INIS)
Stepanets, A I
2001-01-01
Asymptotic equalities are obtained for upper bounds of the deviations of Fourier sums in the classes of convolutions of Poisson kernels and continuous functions with moduli of continuity not exceeding fixed majorants
Appearance of eigen modes for the linearized Vlasov-Poisson equation
International Nuclear Information System (INIS)
Degond, P.
1983-01-01
In order to determine the asymptotic behaviour, when the time goes to infinity, of the solution of the linearized Vlasov-Poisson equation, we use eigen modes, associated to continuous linear functionals on a Banach space of analytic functions [fr
An improved FMM Algorithm of the 3d-linearized Poisson-Boltzmann Equation
Directory of Open Access Journals (Sweden)
Mehrez issa
2015-06-01
Full Text Available This paper presents a new FMM algorithm for the linearized Poisson-Boltzmann equation in three dimensions. The performance of the proposed algorithm is assessed on a example in three dimensions and compared with the direct method. The numerical results show the power of the new method, that allow to achieve the best schemes to reduce the time of the particle interactions, which are based on diagonal form of translation operators for linearized Poisson-Boltzmann equation.
Chadha, Alka; Bora, Swaroop Nandan
2017-11-01
This paper studies the existence, uniqueness, and exponential stability in mean square for the mild solution of neutral second order stochastic partial differential equations with infinite delay and Poisson jumps. By utilizing the Banach fixed point theorem, first the existence and uniqueness of the mild solution of neutral second order stochastic differential equations is established. Then, the mean square exponential stability for the mild solution of the stochastic system with Poisson jumps is obtained with the help of an established integral inequality.
Stochastic Averaging of Strongly Nonlinear Oscillators under Poisson White Noise Excitation
Zeng, Y.; Zhu, W. Q.
A stochastic averaging method for single-degree-of-freedom (SDOF) strongly nonlinear oscillators under Poisson white noise excitation is proposed by using the so-called generalized harmonic functions. The stationary averaged generalized Fokker-Planck-Kolmogorov (GFPK) equation is solved by using the classical perturbation method. Then the procedure is applied to estimate the stationary probability density of response of a Duffing-van der Pol oscillator under Poisson white noise excitation. Theoretical results agree well with Monte Carlo simulations.
He, Meijuan; Xu, Wei; Sun, Zhongkui; Du, Lin
2015-11-01
This paper mainly investigates the phenomenon of stochastic resonance (SR) in a bistable system subjected to Poisson white noise. Statistical complexity measures, as new tools, are first employed to quantify SR phenomenon of given system with Poisson white noise. To begin with, the effect of Poisson white noise on SR phenomenon is studied. The results demonstrate that the curves of statistical complexity measures as a function of Poisson white noise intensity exhibit non-monotonous structure, revealing the existence of SR phenomenon. Besides, it should be noted that small mean arrival rate of Poisson white noise can promote the occurrence of SR. In order to verify the effectiveness of statistical complexity measures, signal-to-noise ratio (SNR) is also calculated. A good agreement among these results obtained by statistical complexity measures and SNR is achieved, which reveals that statistical complexity measures are suitable tools for characterizing SR phenomenon in the presence of Poisson white noise. Then, the effects of amplitude and frequency of different periodic signals, including cosine, rectangular and triangular signal, on SR behavior are investigated, respectively. One can observe that, in the case of same amplitude or frequency of signal, the influence of rectangular signal on SR phenomenon is the most significant among these three signals.
Li, Dongming; Sun, Changming; Yang, Jinhua; Liu, Huan; Peng, Jiaqi; Zhang, Lijuan
2017-04-06
An adaptive optics (AO) system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.
Directory of Open Access Journals (Sweden)
Dongming Li
2017-04-01
Full Text Available An adaptive optics (AO system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.
Mumtaz, Shahzad; Nabney, Ian T; Flower, Darren R
2017-10-01
Peptide-binding MHC proteins are thought the most variable across the human population; the extreme MHC polymorphism observed is functionally important and results from constrained divergent evolution. MHCs have vital functions in immunology and homeostasis: cell surface MHC class I molecules report cell status to CD8+ T cells, NKT cells and NK cells, thus playing key roles in pathogen defence, as well as mediating smell recognition, mate choice, Adverse Drug Reactions, and transplantation rejection. MHC peptide specificity falls into several supertypes exhibiting commonality of binding. It seems likely that other supertypes exist relevant to other functions. Since comprehensive experimental characterization is intractable, structure-based bioinformatics is the only viable solution. We modelled functional MHC proteins by homology and used calculated Poisson-Boltzmann electrostatics projected from the top surface of the MHC as multi-dimensional descriptors, analysing them using state-of-the-art dimensionality reduction techniques and clustering algorithms. We were able to recover the 3 MHC loci as separate clusters and identify clear sub-groups within them, vindicating unequivocally our choice of both data representation and clustering strategy. We expect this approach to make a profound contribution to the study of MHC polymorphism and its functional consequences, and, by extension, other burgeoning structural systems, such as GPCRs. Copyright © 2017 Elsevier Inc. All rights reserved.
Kim, S. Y.; Oh, H. S.; Park, E. S.
2017-10-01
Herein, we elucidate a hidden variable in a shear transformation zone (STZ) volume (Ω) versus Poisson's ratio (ν) relation and clarify the correlation between STZ characteristics and the plasticity of metallic glasses (MGs). On the basis of cooperative shear model and atomic stress theories, we carefully formulate Ω as a function of molar volume (Vm) and ν. The twofold trend in Ω and ν is attributed to a relatively large variation of Vm as compared to that of ν as well as an inverse relation between Vm and ν. Indeed, the derived equation reveals that the number of atoms in an STZ instead of Ω is a microstructural characteristic which has a close relationship with plasticity since it reflects the preference of atomistic behaviors between cooperative shearing and the generation of volume strain fluctuation under stress. The results would deepen our understanding of the correlation between microscopic behaviors (STZ activation) and macroscopic properties (plasticity) in MGs and enable a quantitative approach in associating various STZ-related macroscopic behaviors with intrinsic properties of MGs.
Fetsch, Corinna
2011-09-13
Preparation of defined and functional polymers has been one of the hottest topics in polymer science and drug delivery in the recent decade. Also, research on (bio)degradable polymers gains more and more interest, in particular at the interface of these two disciplines. However, in the majority of cases, combination of definition, functionality and degradability, is problematic. Here we present the preparation and characterization (MALDI-ToF MS, NMR, GPC) of nonionic hydrophilic, hydrophobic, and amphiphilic N-substituted polyglycines (polypeptoids), which are expected to be main-chain degradable and are able to disperse a hydrophobic model compound in aqueous media. Polymerization kinetics suggest that the polymerization is well controlled with strictly linear pseudo first-order kinetic plots to high monomer consumption. Moreover, molar mass distributions of products are Poisson-type and molar mass can be controlled by the monomer to initiator ratio. The presented polymer platform is nonionic, backbone degradable, and synthetically highly flexible and may therefore be valuable for a broad range of applications, in particular as a biomaterial. © 2011 American Chemical Society.
pK(A) in proteins solving the Poisson-Boltzmann equation with finite elements.
Sakalli, Ilkay; Knapp, Ernst-Walter
2015-11-05
Knowledge on pK(A) values is an eminent factor to understand the function of proteins in living systems. We present a novel approach demonstrating that the finite element (FE) method of solving the linearized Poisson-Boltzmann equation (lPBE) can successfully be used to compute pK(A) values in proteins with high accuracy as a possible replacement to finite difference (FD) method. For this purpose, we implemented the software molecular Finite Element Solver (mFES) in the framework of the Karlsberg+ program to compute pK(A) values. This work focuses on a comparison between pK(A) computations obtained with the well-established FD method and with the new developed FE method mFES, solving the lPBE using protein crystal structures without conformational changes. Accurate and coarse model systems are set up with mFES using a similar number of unknowns compared with the FD method. Our FE method delivers results for computations of pK(A) values and interaction energies of titratable groups, which are comparable in accuracy. We introduce different thermodynamic cycles to evaluate pK(A) values and we show for the FE method how different parameters influence the accuracy of computed pK(A) values. © 2015 Wiley Periodicals, Inc.
Modeling Zero-Inflated and Overdispersed Count Data: An Empirical Study of School Suspensions
Desjardins, Christopher David
2016-01-01
The purpose of this article is to develop a statistical model that best explains variability in the number of school days suspended. Number of school days suspended is a count variable that may be zero-inflated and overdispersed relative to a Poisson model. Four models were examined: Poisson, negative binomial, Poisson hurdle, and negative…
Tavala, Amir; Dovzhik, Krishna; Schicker, Klaus; Koschak, Alexandra; Zeilinger, Anton
Probing the visual system of human and animals at very low photon rate regime has recently attracted the quantum optics community. In an experiment on the isolated photoreceptor cells of Xenopus, the cell output signal was measured while stimulating it by pulses with sub-poisson distributed photons. The results showed single photon detection efficiency of 29 +/-4.7% [1]. Another behavioral experiment on human suggests a less detection capability at perception level with the chance of 0.516 +/-0.01 (i.e. slightly better than random guess) [2]. Although the species are different, both biological models and experimental observations with classical light stimuli expect that a fraction of single photon responses is filtered somewhere within the retina network and/or during the neural processes in the brain. In this ongoing experiment, we look for a quantitative answer to this question by measuring the output signals of the last neural layer of WT mouse retina using microelectrode arrays. We use a heralded downconversion single-photon source. We stimulate the retina directly since the eye lens (responsible for 20-50% of optical loss and scattering [2]) is being removed. Here, we demonstrate our first results that confirms the response to the sub-poisson distributied pulses. This project was supported by Austrian Academy of Sciences, SFB FoQuS F 4007-N23 funded by FWF and ERC QIT4QAD 227844 funded by EU Commission.
Qiao, Yan; Xu, Wei; Jia, Wantao; Han, Qun
2017-05-01
Variable-mass systems have received widespread attention and show prominent significance with the explosive development of micro- and nanotechnologies, so there is a growing need to study the influences of mass disturbances on systems. This paper is devoted to investigating the stochastic response of a variable-mass system subject to weakly random excitation, in which the mass disturbance is modeled as a Poisson white noise. Firstly, the original system is approximately replaced by the associated conservative system with small disturbance based on the Taylor expansion technique. Then the stationary response of the approximate system is obtained by applying the stochastic averaging method. At last, a representative variable-mass oscillator is worked out to illustrate the effectiveness of the analytical solution by comparing with Monte Carlo simulation. The relative change of mean-square displacement is used to measure the influences of mass disturbance on system responses. Results reveal that the stochastic responses are more sensitive to mass disturbance for some system parameters. It is also found that the influences of Poisson white noise as the mass disturbance on system responses are significantly different from that of Gaussian white noise of the same intensity.
AbdelNabi, Amr A.
2018-02-12
This paper presents new approaches to characterize the achieved performance of hybrid control-access small cells in the context of two-tier multi-input multi-output (MIMO) cellular networks with random interference distributions. The hybrid scheme at small cells (such as femtocells) allows for sharing radio resources between the two network tiers according to the densities of small cells and their associated users, as well as the observed interference power levels in the two network tiers. The analysis considers MIMO transceivers at all nodes, for which antenna arrays can be utilized to implement transmit antenna selection (TAS) and receive maximal ratio combining (MRC) under MIMO point-to-point channels. Moreover, it tar-gets network-level models of interference sources inside each tier and between the two tiers, which are assumed to follow Poisson field processes. To fully capture the occasions for Poisson field distribution on MIMO spatial domain. Two practical scenarios of interference sources are addressed including highly-correlated or uncorrelated transmit antenna arrays of the serving macrocell base station. The analysis presents new analytical approaches that can characterize the downlink outage probability performance in any tier. Furthermore, the outage performance in high signal-to-noise (SNR) regime is also obtained, which can be useful to deduce diversity and/or coding gains.
Parallel sparse direct solvers for Poisson's equation in streamer discharges
M. Nool (Margreet); M. Genseberger (Menno); U. M. Ebert (Ute)
2017-01-01
textabstractThe aim of this paper is to examine whether a hybrid approach of parallel computing, a combination of the message passing model (MPI) with the threads model (OpenMP) can deliver good performance in streamer discharge simulations. Since one of the bottlenecks of almost all streamer
A novel method for the accurate evaluation of Poisson's ratio of soft polymer materials.
Lee, Jae-Hoon; Lee, Sang-Soo; Chang, Jun-Dong; Thompson, Mark S; Kang, Dong-Joong; Park, Sungchan; Park, Seonghun
2013-01-01
A new method with a simple algorithm was developed to accurately measure Poisson's ratio of soft materials such as polyvinyl alcohol hydrogel (PVA-H) with a custom experimental apparatus consisting of a tension device, a micro X-Y stage, an optical microscope, and a charge-coupled device camera. In the proposed method, the initial positions of the four vertices of an arbitrarily selected quadrilateral from the sample surface were first measured to generate a 2D 1st-order 4-node quadrilateral element for finite element numerical analysis. Next, minimum and maximum principal strains were calculated from differences between the initial and deformed shapes of the quadrilateral under tension. Finally, Poisson's ratio of PVA-H was determined by the ratio of minimum principal strain to maximum principal strain. This novel method has an advantage in the accurate evaluation of Poisson's ratio despite misalignment between specimens and experimental devices. In this study, Poisson's ratio of PVA-H was 0.44 ± 0.025 (n = 6) for 2.6-47.0% elongations with a tendency to decrease with increasing elongation. The current evaluation method of Poisson's ratio with a simple measurement system can be employed to a real-time automated vision-tracking system which is used to accurately evaluate the material properties of various soft materials.
Analysing count data of Butterflies communities in Jasin, Melaka: A Poisson regression analysis
Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Nor, Maria Elena; Mohamed, Maryati; Ismail, Norradihah
2017-09-01
Counting outcomes normally have remaining values highly skewed toward the right as they are often characterized by large values of zeros. The data of butterfly communities, had been taken from Jasin, Melaka and consists of 131 number of subject visits in Jasin, Melaka. In this paper, considering the count data of butterfly communities, an analysis is considered Poisson regression analysis as it is assumed to be an alternative way on better suited to the counting process. This research paper is about analysing count data from zero observation ecological inference of butterfly communities in Jasin, Melaka by using Poisson regression analysis. The software for Poisson regression is readily available and it is becoming more widely used in many field of research and the data was analysed by using SAS software. The purpose of analysis comprised the framework of identifying the concerns. Besides, by using Poisson regression analysis, the study determines the fitness of data for accessing the reliability on using the count data. The finding indicates that the highest and lowest number of subject comes from the third family (Nymphalidae) family and fifth (Hesperidae) family and the Poisson distribution seems to fit the zero values.
A regularization method for solving the Poisson equation for mixed unbounded-periodic domains
Juul Spietz, Henrik; Mølholm Hejlesen, Mads; Walther, Jens Honoré
2018-03-01
Regularized Green's functions for mixed unbounded-periodic domains are derived. The regularization of the Green's function removes its singularity by introducing a regularization radius which is related to the discretization length and hence imposes a minimum resolved scale. In this way the regularized unbounded-periodic Green's functions can be implemented in an FFT-based Poisson solver to obtain a convergence rate corresponding to the regularization order of the Green's function. The high order is achieved without any additional computational cost from the conventional FFT-based Poisson solver and enables the calculation of the derivative of the solution to the same high order by direct spectral differentiation. We illustrate an application of the FFT-based Poisson solver by using it with a vortex particle mesh method for the approximation of incompressible flow for a problem with a single periodic and two unbounded directions.
DEFF Research Database (Denmark)
Hejlesen, Mads Mølholm
A regularisation method for solving the Poisson equation using Green’s functions is presented.The method is shown to obtain a convergence rate which corresponds to the design of the regularised Green’s function and a spectral-like convergence rate is obtained using a spectrally ideal regularisation....... It is shown that the regularised Poisson solver can be extended to handle mixed periodic and free-space boundary conditions. This is done by solving the equation spectrally in the periodic directions which yields a modified Helmholtz equation for the free-space directions which in turn is solved by deriving...... the appropriate regularised Green’s functions. Using an analogy to the particle-particle particle-mesh method, a framework for calculating multi-resolution solutions using local refinement patches is presented. The regularised Poisson solver is shown to maintain a high order converging solution for different...
PB-AM: An open-source, fully analytical linear poisson-boltzmann solver
Energy Technology Data Exchange (ETDEWEB)
Felberg, Lisa E. [Department of Chemical and Biomolecular Engineering, University of California Berkeley, Berkeley California 94720; Brookes, David H. [Department of Chemistry, University of California Berkeley, Berkeley California 94720; Yap, Eng-Hui [Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx New York 10461; Jurrus, Elizabeth [Division of Computational and Statistical Analytics, Pacific Northwest National Laboratory, Richland Washington 99352; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City Utah 84112; Baker, Nathan A. [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, Richland Washington 99352; Division of Applied Mathematics, Brown University, Providence Rhode Island 02912; Head-Gordon, Teresa [Department of Chemical and Biomolecular Engineering, University of California Berkeley, Berkeley California 94720; Department of Chemistry, University of California Berkeley, Berkeley California 94720; Department of Bioengineering, University of California Berkeley, Berkeley California 94720; Chemical Sciences Division, Lawrence Berkeley National Labs, Berkeley California 94720
2016-11-02
We present the open source distributed software package Poisson-Boltzmann Analytical Method (PB-AM), a fully analytical solution to the linearized Poisson Boltzmann equation. The PB-AM software package includes the generation of outputs files appropriate for visualization using VMD, a Brownian dynamics scheme that uses periodic boundary conditions to simulate dynamics, the ability to specify docking criteria, and offers two different kinetics schemes to evaluate biomolecular association rate constants. Given that PB-AM defines mutual polarization completely and accurately, it can be refactored as a many-body expansion to explore 2- and 3-body polarization. Additionally, the software has been integrated into the Adaptive Poisson-Boltzmann Solver (APBS) software package to make it more accessible to a larger group of scientists, educators and students that are more familiar with the APBS framework.
Switching Induced by Poisson Radio-Frequency Pulses in Nonlinear Micromechanical Oscillators
Zou, Jie; Buvaev, Sanal; Chan, H. B.
2010-03-01
We study switching induced by Poisson radio-frequency (RF) pulses in nonlinear micromechanical oscillators. Under sufficiently large periodic excitation, nonlinear micromechanical oscillators possess multiple oscillation states with different amplitudes. The presence of noise enables the system to switch between these states. We find that in the vicinity of the bifurcation point the activation barrier, which is given by the logarithm of the switching rate, has a logarithmic dependence on the mean rate of Poisson RF pulses. Moreover, the measured dependence of the activation barrier on the distance to the saddle-node bifurcation η is consistent with predicted universal scaling relationships. While for white Gaussian noise the activation barrier shows a clean 3/2 power-law dependence on η, for modulated Poisson pulses the power-law has a different power of 1/2 with an additional logarithmic factor. Our measured critical exponents are in accordance with theoretical predictions.
Fiber-wise linear Poisson structures related to W∗-algebras
Odzijewicz, Anatol; Jakimowicz, Grzegorz; Sliżewska, Aneta
2018-01-01
In the framework of Banach differential geometry we investigate the fiber-wise linear Poisson structures as well as the Lie groupoid and Lie algebroid structures which are defined in the canonical way by the structure of a W∗-algebra (von Neumann algebra) M. The main role in this theory is played by the complex Banach-Lie groupoid G(M) ⇉ L(M) of partially invertible elements of M over the lattice L(M) of orthogonal projections of M. The Atiyah sequence and the predual Atiyah sequence corresponding to this groupoid are investigated from the point of view of Banach Poisson geometry. In particular we show that the predual Atiyah sequence fits in a short exact sequence of complex Banach sub-Poisson V B-groupoids with G(M) ⇉ L(M) as the side groupoid.
Infinitesimal deformations of Poisson bi-vectors using the Kontsevich graph calculus
Buring, Ricardo; Kiselev, Arthemy V.; Rutten, Nina
2018-02-01
Let \\mathscr{P} be a Poisson structure on a finite-dimensional affine real manifold. Can \\mathscr{P} be deformed in such a way that it stays Poisson? The language of Kontsevich graphs provides a universal approach - with respect to all affine Poisson manifolds - to finding a class of solutions to this deformation problem. For that reasoning, several types of graphs are needed. In this paper we outline the algorithms to generate those graphs. The graphs that encode deformations are classified by the number of internal vertices k; for k ≤ 4 we present all solutions of the deformation problem. For k ≥ 5, first reproducing the pentagon-wheel picture suggested at k = 6 by Kontsevich and Willwacher, we construct the heptagon-wheel cocycle that yields a new unique solution without 2-loops and tadpoles at k = 8.
Pêche thonière et dispositifs de concentration de poissons
Le Gall, Jean-yves; Cayre, Patrice; Taquet, Marc
2000-01-01
Le colloque international « Pêche thonière et dispositifs de concentration de poissons» organisé en octobre 1999, en Martinique, permet de dresser un bilan, sous forme de synthèses régionales, de l'exploitation des grands poissons pélagiques à l'aide de DCP dans les trois océans et en Méditerranée. La technologie, les méthodes de pêche, l'impact sur les ressources, le comportement agrégatif des poissons et les aspects socio-économiques de l'utilisation des DCP sont les principaux thèmes dével...
Bouleau, Nicolas
2015-01-01
A simplified approach to Malliavin calculus adapted to Poisson random measures is developed and applied in this book. Called the “lent particle method” it is based on perturbation of the position of particles. Poisson random measures describe phenomena involving random jumps (for instance in mathematical finance) or the random distribution of particles (as in statistical physics). Thanks to the theory of Dirichlet forms, the authors develop a mathematical tool for a quite general class of random Poisson measures and significantly simplify computations of Malliavin matrices of Poisson functionals. The method gives rise to a new explicit calculus that they illustrate on various examples: it consists in adding a particle and then removing it after computing the gradient. Using this method, one can establish absolute continuity of Poisson functionals such as Lévy areas, solutions of SDEs driven by Poisson measure and, by iteration, obtain regularity of laws. The authors also give applications to error calcul...
Tuckwell, H C; Walsh, J B
1983-01-01
The linear cable equation with uniform Poisson or white noise input current is employed as a model for the voltage across the membrane of a one-dimensional nerve cylinder, which may sometimes represent the dendritic tree of a nerve cell. From the Green's function representation of the solutions, the mean, variance and covariance of the voltage are found. At large times, the voltage becomes asymptotically wide-sense stationary and we find the spectral density functions for various cable lengths and boundary conditions. For large frequencies the voltage exhibits "1/f3/2 noise". Using the Fourier series representation of the voltage we study the moments of the firing times for the diffusion model with numerical techniques, employing a simplified threshold criterion. We also simulate the solution of the stochastic cable equation by two different methods in order to estimate the moments and density of the firing time.
Is neutron evaporation from highly excited nuclei a poisson random process
International Nuclear Information System (INIS)
Simbel, M.H.
1982-01-01
It is suggested that neutron emission from highly excited nuclei follows a Poisson random process. The continuous variable of the process is the excitation energy excess over the binding energy of the emitted neutrons and the discrete variable is the number of emitted neutrons. Cross sections for (HI,xn) reactions are analyzed using a formula containing a Poisson distribution function. The post- and pre-equilibrium components of the cross section are treated separately. The agreement between the predictions of this formula and the experimental results is very good. (orig.)
International Nuclear Information System (INIS)
Lacombe, J.P.
1985-12-01
Statistic study of Poisson non-homogeneous and spatial processes is the first part of this thesis. A Neyman-Pearson type test is defined concerning the intensity measurement of these processes. Conditions are given for which consistency of the test is assured, and others giving the asymptotic normality of the test statistics. Then some techniques of statistic processing of Poisson fields and their applications to a particle multidetector study are given. Quality tests of the device are proposed togetherwith signal extraction methods [fr
Linear stability of stationary solutions of the Vlasov-Poisson system in three dimensions
Energy Technology Data Exchange (ETDEWEB)
Batt, J.; Rein, G. [Muenchen Univ. (Germany). Mathematisches Inst.; Morrison, P.J. [Texas Univ., Austin, TX (United States)
1993-03-01
Rigorous results on the stability of stationary solutions of the Vlasov-Poisson system are obtained in both the plasma physics and stellar dynamics contexts. It is proven that stationary solutions in the plasma physics (stellar dynamics) case are linearly stable if they are decreasing (increasing) functions of the local, i.e. particle, energy. The main tool in the analysis is the free energy of the system, a conserved quantity. In addition, an appropriate global existence result is proven for the linearized Vlasov-Poisson system and the existence of stationary solutions that satisfy the above stability condition is established.
Random vibrations of Rayleigh vibroimpact oscillator under Parametric Poisson white noise
Yang, Guidong; Xu, Wei; Jia, Wantao; He, Meijuan
2016-04-01
Random vibration problems for a single-degree-of-freedom (SDOF) Rayleigh vibroimpact system with a rigid barrier under parametric Poisson white noise are considered. The averaged generalized Fokker-Planck-Kolmogorov (FPK) equations with parametric Poisson white noise are derived after using the nonsmooth variable transformation and the approximate stationary solutions for the system's response are obtained by perturbation method. The results are validated numerically by using Monte Carlo simulations from original vibroimpact system. Effects on the response for different damping coefficients, restitution coefficients and noise intensities are discussed. Furthermore, stochastic bifurcations are also explored.
The effects of filament magnetization in superconducting magnets as calculated by POISSON
International Nuclear Information System (INIS)
Caspi, S.; Gilbert, W.S.; Helm, M.; Laslett, L.J.
1986-09-01
Magnetization of superconducting material can be introduced into POISSON through a field dependent permeability table (in the same way that iron characteristics are introduced). This can be done by representing measured magnetization data of the increasing and decreasing field by two independent B-γ curves (γ = 1/μ). Magnetization curves of this type were incorporated into the current regions of the program POISSON and their effect on the field coefficients observed. We have used this technique to calculate the effect of magnetization on the multipole coefficients of a SSC superconducting dipole magnet and to compare these coefficients with measured values
Fast immersed interface Poisson solver for 3D unbounded problems around arbitrary geometries
Gillis, T.; Winckelmans, G.; Chatelain, P.
2018-02-01
We present a fast and efficient Fourier-based solver for the Poisson problem around an arbitrary geometry in an unbounded 3D domain. This solver merges two rewarding approaches, the lattice Green's function method and the immersed interface method, using the Sherman-Morrison-Woodbury decomposition formula. The method is intended to be second order up to the boundary. This is verified on two potential flow benchmarks. We also further analyse the iterative process and the convergence behavior of the proposed algorithm. The method is applicable to a wide range of problems involving a Poisson equation around inner bodies, which goes well beyond the present validation on potential flows.
Observable currents and a covariant Poisson algebra of physical observables
Díaz-Marín, Homero G.; Zapata, José A.
2017-01-01
Observable currents are conserved gauge invariant currents; physical observables may be calculated integrating them on appropriate hypersurfaces. Due to the conservation law the hypersurfaces become irrelevant up to homology, and the main objects of interest become the observable currents them selves. Gauge inequivalent solutions can be distinguished by means of observable currents. With the aim of modelling spacetime local physics, we work on spacetime domains $U\\subset M$ which may have bou...
e+-e- hadronic multiplicity distributions: negative binomial or Poisson
International Nuclear Information System (INIS)
Carruthers, P.; Shih, C.C.
1986-01-01
On the basis of fits to the multiplicity distributions for variable rapidity windows and the forward backward correlation for the 2 jet subset of e + e - data it is impossible to distinguish between a global negative binomial and its generalization, the partially coherent distribution. It is suggested that intensity interferometry, especially the Bose-Einstein correlation, gives information which will discriminate among dynamical models. 16 refs
Sensitivity Study of Poisson's Ratio Used in Soil Structure Interaction (SSI) Analyses
Energy Technology Data Exchange (ETDEWEB)
Han, Seung-ju [KHNP CRI, Daejeon (Korea, Republic of); You, Dong-Hyun [KEPCO Engineering and Construction, Gimcheon (Korea, Republic of); Jang, Jung-bum; Yun, Kwan-hee [KEPCO Research Institute, Daejeon (Korea, Republic of)
2016-10-15
The preliminary review for Design Certification (DC) of APR1400 was accepted by NRC on March 4, 2015. After the acceptance of the application for standard DC of APR1400, KHNP has responded the Request for Additional Information (RAI) raised by NRC to undertake a full design certification review. Design certification is achieved through the NRC's rulemaking process, and is founded on the staff's review of the application, which addresses the various safety issues associated with the proposed nuclear power plant design, independent of a specific site. The USNRC issued RAIs pertain to Design Control Document (DCD) Ch.3.7 'Seismic Design' is DCD Tables 3.7A-1 and 3.7A-2 show Poisson’s ratios in the S1 and S2 soil profiles used for SSI analysis as great as 0.47 and 0.48 respectively. Based on staff experience, use of Poisson's ratio approaching these values may result in numerical instability of the SSI analysis results. Sensitivity study is performed using the ACS SASSI NI model of APR1400 with S1 and S2 soil profiles to demonstrate that the Poisson’s ratio values used in the SSI analyses of S1 and S2 soil profile cases do not produce numerical instabilities in the SSI analysis results. No abrupt changes or spurious peaks, which tend to indicate existence of numerical sensitivities in the SASSI solutions, appear in the computed transfer functions of the original SSI analyses that have the maximum dynamic Poisson’s ratio values of 0.47 and 0.48 as well as in the re-computed transfer functions that have the maximum dynamic Poisson’s ratio values limited to 0.42 and 0.45.
Poisson regression analysis of the mortality among a cohort of World War II nuclear industry workers
International Nuclear Information System (INIS)
Frome, E.L.; Cragle, D.L.; McLain, R.W.
1990-01-01
A historical cohort mortality study was conducted among 28,008 white male employees who had worked for at least 1 month in Oak Ridge, Tennessee, during World War II. The workers were employed at two plants that were producing enriched uranium and a research and development laboratory. Vital status was ascertained through 1980 for 98.1% of the cohort members and death certificates were obtained for 96.8% of the 11,671 decedents. A modified version of the traditional standardized mortality ratio (SMR) analysis was used to compare the cause-specific mortality experience of the World War II workers with the U.S. white male population. An SMR and a trend statistic were computed for each cause-of-death category for the 30-year interval from 1950 to 1980. The SMR for all causes was 1.11, and there was a significant upward trend of 0.74% per year. The excess mortality was primarily due to lung cancer and diseases of the respiratory system. Poisson regression methods were used to evaluate the influence of duration of employment, facility of employment, socioeconomic status, birth year, period of follow-up, and radiation exposure on cause-specific mortality. Maximum likelihood estimates of the parameters in a main-effects model were obtained to describe the joint effects of these six factors on cause-specific mortality of the World War II workers. We show that these multivariate regression techniques provide a useful extension of conventional SMR analysis and illustrate their effective use in a large occupational cohort study
Ibrahim, R. S.; El-Kalaawy, O. H.
2006-10-01
The relativistic nonlinear self-consistent equations for a collisionless cold plasma with stationary ions [R. S. Ibrahim, IMA J. Appl. Math. 68, 523 (2003)] are extended to 3 and 3+1 dimensions. The resulting system of equations is reduced to the sine-Poisson equation. The truncated Painlevé expansion and reduction of the partial differential equation to a quadrature problem (RQ method) are described and applied to obtain the traveling wave solutions of the sine-Poisson equation for stationary and nonstationary equations in 3 and 3+1 dimensions describing the charge-density equilibrium configuration model.
Intégration d'insectes aux aliments pour la volaille et le poisson, au ...
International Development Research Centre (IDRC) Digital Library (Canada)
Dans de nombreux pays africains, les industries avicoles et piscicoles comptent parmi les agroentreprises qui affichent la croissance la plus rapide. Toutefois, les ingrédients coûteux, comme le poisson et les végétaux, qui entrent dans la composition des aliments pour animaux menacent la survie des exploitants. Ce projet ...
C1-continuous Virtual Element Method for Poisson-Kirchhoff plate problem
Energy Technology Data Exchange (ETDEWEB)
Gyrya, Vitaliy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Mourad, Hashem Mohamed [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-09-20
We present a family of C1-continuous high-order Virtual Element Methods for Poisson-Kirchho plate bending problem. The convergence of the methods is tested on a variety of meshes including rectangular, quadrilateral, and meshes obtained by edge removal (i.e. highly irregular meshes). The convergence rates are presented for all of these tests.
Upper limit for Poisson variable incorporating systematic uncertainties by Bayesian approach
International Nuclear Information System (INIS)
Zhu, Yongsheng
2007-01-01
To calculate the upper limit for the Poisson observable at given confidence level with inclusion of systematic uncertainties in background expectation and signal efficiency, formulations have been established along the line of Bayesian approach. A FORTRAN program, BPULE, has been developed to implement the upper limit calculation
A direct Poisson solver for Particle-In-Cell (PIC) simulation
International Nuclear Information System (INIS)
Tran, T.M.; Appert, K.; Sauter, O.
1994-09-01
A direct Poisson solver, based on the isoparametric finite element discretization and a domain decomposition technique, is described. A simple parallelization scheme is proposed and evaluated on a 128 processor Cray T3D. (author) 4 figs., 2 tabs., 8 refs
A note on the time decay of solutions for the linearized Wigner-Poisson system
Gamba, Irene
2009-01-01
We consider the one-dimensional Wigner-Poisson system of plasma physics, linearized around a (spatially homogeneous) Lorentzian distribution and prove that the solution of the corresponding linearized problem decays to zero in time. We also give an explicit algebraic decay rate.
A modified SOR method for the Poisson equation in unsteady free-surface flow calculations.
Botta, E.F.F.; Ellenbroek, Marcellinus Hermannus Maria
1985-01-01
Convergence difficulties that sometimes occur if the successive overrelaxation (SOR) method is applied to the Poisson equation on a region with irregular free boundaries are analyzed. It is shown that these difficulties are related to the treatment of the free boundaries and caused by the appearance
The Integral Equation Method and the Neumann Problem for the Poisson Equation on NTA Domains
Czech Academy of Sciences Publication Activity Database
Medková, Dagmar
2009-01-01
Roč. 63, č. 21 (2009), s. 227-247 ISSN 0378-620X Institutional research plan: CEZ:AV0Z10190503 Keywords : Poisson equation * Neumann problem * integral equation method Subject RIV: BA - General Mathematics Impact factor: 0.477, year: 2009
Which solutions of the third problem for the Poisson equation are bounded?
Czech Academy of Sciences Publication Activity Database
Medková, Dagmar
-, č. 6 (2004), s. 501-510 ISSN 1085-3375 R&D Projects: GA ČR GA201/00/1515 Institutional research plan: CEZ:AV0Z1019905 Keywords : Poisson equation * Robin problem * boundedness Subject RIV: BA - General Mathematics
TCP (truncated compound poisson) process for multiplicity distributions in high energy collisions
International Nuclear Information System (INIS)
Srivastava, P.P.
1989-01-01
On using the Poisson distribution truncated at zero for intermediate cluster decay in a compound Poisson process we obtain TCP distribution which describes quite well the multiplicity distributions in high energy collisions. A detailed comparison is made between TCP and NB for UA5 data. The reduced moments up to the fifth agree very well with the observed ones. The TCP curves are narrower than NB at high multiplicity tail, look narrower at very high energy and develop shoulders and oscillations which become increasingly pronounced as the energy grows. At lower energies the curves are very close to the NB ones. We also compare the parameterizations by these two distributions of the data for fixed intervals of rapidity for UA5 data and for the data (at low energy) for e sup(+) e sup(-) annihilati8on and pion-proton, discussion of compound Poisson distribution expressions of reduced moments and Poisson transforms are also given. The TCP curves and curves of the reduced moments for different values of the parameters are also presented. (author)
Poisson noise reduction from X-ray images by region classification ...
Indian Academy of Sciences (India)
Thakur Kirti
Department of Electronics and Telecommunication Engineering, College of Engineering, Pune 411005, India e-mail: kirti79@gmail.com. MS received 18 May 2015; revised 28 November 2016; accepted 7 January 2017. Abstract. Medical imaging is perturbed with inherent noise such as speckle noise in ultrasound, Poisson ...
Poisson noise reduction from X-ray images by region classification ...
Indian Academy of Sciences (India)
Medical imaging is perturbed with inherent noise such as speckle noise in ultrasound, Poisson noise in X-ray and Rician noise in MRI imaging. This paper focuses on X-ray image denoising problem. X-ray image quality could be improved by increasing dose value; however, this may result in cell death or similar kinds of ...
General solution of Poisson equation in three dimensions for disk-like galaxies
International Nuclear Information System (INIS)
Tong, Y.; Zheng, X.; Peng, O.
1982-01-01
The general solution of the Poisson equation is solved by means of integral transformations for Vertical BarkVertical Barr>>1 provided that the perturbed density of disk-like galaxies distributes along the radial direction according to the Hankel function. This solution can more accurately represent the outer spiral arms of disk-like galaxies
Mei, Li; van der Mei, Henny C.; Ren, Yijin; Norde, Willem; Busscher, Henk J.
2009-01-01
Poisson analysis of retract force-distance curves in atomic force microscopy (AFM) has yielded a new dimension to the decoupling of individual bond forces into a hydrogen bonding and nonspecific force component. Accordingly, bacterial adhesion forces have been decoupled into a hydrogen bonding and
The Poisson algebra of the invariant charges of the Nambu-Goto theory: Casimir elements
International Nuclear Information System (INIS)
Pohlmeyer, K.
1988-01-01
The reparametrization invariant ''non-local'' conserved charges of the Nambu-Goto theory form an algebra under Poisson bracket operation. The center of the formal closure of this algebra is determined. The relation of the central elements to the constraints of the Nambu-Goto theory is clarified. (orig.)
On two-echelon inventory systems with Poisson demand and lost sales
Alvarez, Elisa; van der Heijden, Matthijs C.
2014-01-01
We consider a two-echelon, continuous review inventory system under Poisson demand and a one-for-one replenishment policy. Demand is lost if no items are available at the local warehouse, the central depot, or in the pipeline in between. We give a simple, fast and accurate approach to approximate
A note on influence of stress anisotropy on the Poisson's ratio of dry sand
Directory of Open Access Journals (Sweden)
Huan He
2017-12-01
Full Text Available In this study, extender and bender element tests were conducted investigating the small-strain Poisson's ratio of variable sands, with a focus on the effect of stress anisotropy in order to quantify the sensitivity of Poisson's ratio to the applied deviatoric stress. Four different uniform sands were tested, including a biogenic sand, a crushed rock and two natural sands, covering a wide range of particle shapes. From these sands, eleven samples were prepared in the laboratory and were tested under variable stress paths, maintaining a constant mean effective pressure while increasing the deviatoric compressive load. Under the application of these given stress paths, the data analysis indicated that the sensitivity of Poisson's ratio to the stress ratio was more pronounced for sands with irregularly shaped particles in comparison to sands with fairly rounded and spherical grains. For sands with very irregularly shaped particles, the increase of Poisson's ratio from the isotropic to the anisotropic stress state reached 50%, while this increase for natural sands with fairly rounded particles was in the order of 20%.
Teunter, Ruud H.; Haneveld, Willem K. Klein
2008-01-01
We study inventory systems with two demand classes (critical and non-critical), Poisson demand and backordering. We analyze dynamic rationing strategies where the number of items reserved for critical demand depends on the remaining time until the next order arrives. Different from results in the
Directory of Open Access Journals (Sweden)
V.Dorvilien
2013-01-01
Full Text Available The structure of cylindrical double layers is studied using a modified Poisson Boltzmann theory and the density functional approach. In the model double layer the electrode is a cylindrical polyion that is infinitely long, impenetrable, and uniformly charged. The polyion is immersed in a sea of equi-sized rigid ions embedded in a dielectric continuum. An in-depth comparison of the theoretically predicted zeta potentials, the mean electrostatic potentials, and the electrode-ion singlet density distributions is made with the corresponding Monte Carlo simulation data. The theories are seen to be consistent in their predictions that include variations in ionic diameters, electrolyte concentrations, and electrode surface charge densities, and are also able to reproduce well some new and existing Monte Carlo results.
Coverage maximization for a poisson field of drone cells
Azari, Mohammad Mahdi
2018-02-15
The use of drone base stations to provide wireless connectivity for ground terminals is becoming a promising part of future technologies. The design of such aerial networks is however different compared to cellular 2D networks, as antennas from the drones are looking down, and the channel model becomes height-dependent. In this paper, we study the effect of antenna patterns and height-dependent shadowing. We consider a random network topology to capture the effect of dynamic changes of the flying base stations. First we characterize the aggregate interference imposed by the co-channel neighboring drones. Then we derive the link coverage probability between a ground user and its associated drone base station. The result is used to obtain the optimum system parameters in terms of drones antenna beamwidth, density and altitude. We also derive the average LoS probability of the associated drone and show that it is a good approximation and simplification of the coverage probability in low altitudes up to 500 m according to the required signal-to-interference-plus-noise ratio (SINR).
International Nuclear Information System (INIS)
Ka-Lin, Su; Yuan-Xi, Xie
2010-01-01
By introducing a more general auxiliary ordinary differential equation (ODE), a modified variable separated ordinary differential equation method is presented for solving the (2 + 1)-dimensional sine-Poisson equation. As a result, many explicit and exact solutions of the (2 + 1)-dimensional sine-Poisson equation are derived in a simple manner by this technique. (general)
Michael, A. J.
2012-12-01
Detecting trends in the rate of sporadic events is a problem for earthquakes and other natural hazards such as storms, floods, or landslides. I use synthetic events to judge the tests used to address this problem in seismology and consider their application to other hazards. Recent papers have analyzed the record of magnitude ≥7 earthquakes since 1900 and concluded that the events are consistent with a constant rate Poisson process plus localized aftershocks (Michael, GRL, 2011; Shearer and Stark, PNAS, 2012; Daub et al., GRL, 2012; Parsons and Geist, BSSA, 2012). Each paper removed localized aftershocks and then used a different suite of statistical tests to test the null hypothesis that the remaining data could be drawn from a constant rate Poisson process. The methods include KS tests between event times or inter-event times and predictions from a Poisson process, the autocorrelation function on inter-event times, and two tests on the number of events in time bins: the Poisson dispersion test and the multinomial chi-square test. The range of statistical tests gives us confidence in the conclusions; which are robust with respect to the choice of tests and parameters. But which tests are optimal and how sensitive are they to deviations from the null hypothesis? The latter point was raised by Dimer (arXiv, 2012), who suggested that the lack of consideration of Type 2 errors prevents these papers from being able to place limits on the degree of clustering and rate changes that could be present in the global seismogenic process. I produce synthetic sets of events that deviate from a constant rate Poisson process using a variety of statistical simulation methods including Gamma distributed inter-event times and random walks. The sets of synthetic events are examined with the statistical tests described above. Preliminary results suggest that with 100 to 1000 events, a data set that does not reject the Poisson null hypothesis could have a variability that is 30% to
Berlin, Conny; Blanch, Carles; Lewis, David J; Maladorno, Dionigi D; Michel, Christiane; Petrin, Michael; Sarp, Severine; Close, Philippe
2012-06-01
The detection of safety signals with medicines is an essential activity to protect public health. Despite widespread acceptance, it is unclear whether recently applied statistical algorithms provide enhanced performance characteristics when compared with traditional systems. Novartis has adopted a novel system for automated signal detection on the basis of disproportionality methods within a safety data mining application (Empirica™ Signal System [ESS]). ESS uses two algorithms for routine analyses: empirical Bayes Multi-item Gamma Poisson Shrinker and logistic regression (LR). A model was developed comprising 14 medicines, categorized as "new" or "established." A standard was prepared on the basis of safety findings selected from traditional sources. ESS results were compared with the standard to calculate the positive predictive value (PPV), specificity, and sensitivity. PPVs of the lower one-sided 5% and 0.05% confidence limits of the Bayes geometric mean (EB05) and of the LR odds ratio (LR0005) almost coincided for all the drug-event combinations studied. There was no obvious difference comparing the PPV of the leading Medical Dictionary for Regulatory Activities (MedDRA) terms to the PPV for all terms. The PPV of narrow MedDRA query searches was higher than that for broad searches. The widely used threshold value of EB05 = 2.0 or LR0005 = 2.0 together with more than three spontaneous reports of the drug-event combination produced balanced results for PPV, sensitivity, and specificity. Consequently, performance characteristics were best for leading terms with narrow MedDRA query searches irrespective of applying Multi-item Gamma Poisson Shrinker or LR at a threshold value of 2.0. This research formed the basis for the configuration of ESS for signal detection at Novartis. Copyright © 2011 John Wiley & Sons, Ltd.
A Fast Poisson Solver with Periodic Boundary Conditions for GPU Clusters in Various Configurations
Rattermann, Dale Nicholas
Fast Poisson solvers using the Fast Fourier Transform on uniform grids are especially suited for parallel implementation, making them appropriate for portability on graphical processing unit (GPU) devices. The goal of the following work was to implement, test, and evaluate a fast Poisson solver for periodic boundary conditions for use on a variety of GPU configurations. The solver used in this research was FLASH, an immersed-boundary-based method, which is well suited for complex, time-dependent geometries, has robust adaptive mesh refinement/de-refinement capabilities to capture evolving flow structures, and has been successfully implemented on conventional, parallel supercomputers. However, these solvers are still computationally costly to employ, and the total solver time is dominated by the solution of the pressure Poisson equation using state-of-the-art multigrid methods. FLASH improves the performance of its multigrid solvers by integrating a parallel FFT solver on a uniform grid during a coarse level. This hybrid solver could then be theoretically improved by replacing the highly-parallelizable FFT solver with one that utilizes GPUs, and, thus, was the motivation for my research. In the present work, the CPU-utilizing parallel FFT solver (PFFT) used in the base version of FLASH for solving the Poisson equation on uniform grids has been modified to enable parallel execution on CUDA-enabled GPU devices. New algorithms have been implemented to replace the Poisson solver that decompose the computational domain and send each new block to a GPU for parallel computation. One-dimensional (1-D) decomposition of the computational domain minimizes the amount of network traffic involved in this bandwidth-intensive computation by limiting the amount of all-to-all communication required between processes. Advanced techniques have been incorporated and implemented in a GPU-centric code design, while allowing end users the flexibility of parameter control at runtime in
Observations sur Saprolegnia australis Elliott, agent pathogène de la saprolegniose des poissons
Directory of Open Access Journals (Sweden)
PAPATHEODOROU B. T.
1981-10-01
Full Text Available Saprolegnia australis n'a jamais été rapporté comme cause primaire de la Saprolegniose chez les poissons et son pouvoir pathogène n'a jamais été vérifié par inoculation expérimentale. Nous l'avons isolé sur des gardons (Rutilus rutilus L. atteints d'une mycose et nous l'avons inoculé avec succès à des poissons exotiques. Nous avons ainsi vérifié le potentiel pathogène de cette espèce de champignon et pu établir avec certitude une causalité entre la seule présence de S. australis et la Saprolegniose observée.
Mascarenhas, N D A; Cruvinel, P E
1999-01-01
A minitomograph scanner for soil science was developed by the National Center for Research and Development of Agricultural Instrumentation (EMBRAPA/CNPDIA). The purpose of this paper is twofold. First, a statistical characterization of the noise affecting the projection measurements of this scanner is presented. Second, having determined the Poisson nature of this noise, a new method of filtering the projection data prior to the reconstruction is proposed. It is based on transforming the Poisson noise into Gaussian additive noise, filtering the projections in blocks through the Wiener filter and performing the inverse tranformation. Results with real data indicate that this method gives superior results, as compared to conventional backprojection with the ramp filter, by taking into consideration both resolution and noise, through a mean square error criterion.
A Criterium for the Strict Positivity of the Density of the Law of a Poisson Process
Directory of Open Access Journals (Sweden)
Léandre Rémi
2011-01-01
Full Text Available We translate in semigroup theory our result (Léandre, 1990 giving a necessary condition so that the law of a Markov process with jumps could have a strictly positive density. This result express, that we have to jump in a finite number of jumps in a "submersive" way from the starting point to the end point if the density of the jump process is strictly positive in . We use the Malliavin Calculus of Bismut type of (Léandre, (2008;2010 translated in semi-group theory as a tool, and the interpretation in semi-group theory of some classical results of the stochastic analysis for Poisson process as, for instance, the formula giving the law of a compound Poisson process.
International Nuclear Information System (INIS)
Sharifi, M. J.; Adibi, A.
2000-01-01
In this paper, we have extended and completed our previous work, that was introducing a new method for finite differentiation. We show the applicability of the method for solving a wide variety of equations such as poisson, Laplace and Schrodinger. These equations are fundamental to the most semiconductor device simulators. In a section, we solve the Shordinger equation by this method in several cases including the problem of finding electron concentration profile in the channel of a HEMT. In another section, we solve the Poisson equation by this method, choosing the problem of SBD as an example. Finally we solve the Laplace equation in two dimensions and as an example, we focus on the VED. In this paper, we have shown that, the method can get stable and precise results in solving all of these problems. Also the programs which have been written based on this method become considerably faster, more clear, and more abstract