搜索结果: 1-14 共查到“统计学其他学科 Stochastic”相关记录14条 . 查询时间(0.125 秒)
A population Monte Carlo scheme with transformed weights and its application to stochastic kinetic models
Population Monte Carlo importance sampling degeneracy of importance weights stochastic kinetic models
2012/9/18
This paper addresses the problem of Monte Carlo approximation of posterior probability distributions. In particular, we have considered a recently proposed technique known as population Monte Carlo (P...
A stochastic variational framework for fitting and diagnosing generalized linear mixed models
Hierarchical model Identify divergent units Large longitudinal data Non-conjugate model Stochastic approximation Variational Bayes
2012/9/17
Variational Bayes computational methods are attracting increasing in-terest because of their ability to scale to large data sets. Here, application of the
non-conjugate variational message passing (N...
Inverse Modeling of Dynamical Systems: Multi-Dimensional Extensions of a Stochastic Switching Problem
Inverse Modeling of Dynamical Systems Multi-Dimensional Extensions Stochastic Switching Problem
2012/9/18
The Buridan's ass paradox is characterized by perpetual indecision between two states, which are never attained. When this problem is formulated as a dynamical
system, indecision is modeled by a disc...
The use of systems of stochastic PDEs as priors for multivariate models with discrete structures
Gaussian distribution multivariate stochastic PDEs discrete structures
2012/9/17
A challenge in multivariate problems with discrete structures is the inclusion of prior information that may di er in each separate structure. A particular example of this is seismic amplitude versus ...
Stochastic optimization and sparse statistical recovery: An optimal algorithm for high dimensions
Stochastic optimization sparse statistical recovery optimal algorithm high dimensions
2012/9/19
We develop and analyze stochastic optimization algorithms for problems in which the ex-pected loss is strongly convex, and the optimum is (approximately)sparse. Previous approaches are able to exploit...
Stochastic particle packing with specified granulometry and porosity
granular media simulation particulate systems particle generation point processess
2012/9/19
This work presents a technique for particle size generation and placement in arbitrary closed domains. Its main application is the simulation of granular media described by disks. Particle size genera...
Hypothesis Testing in Speckled Data with Stochastic Distances
image analysis information theory SAR im-agery speckle noise multiplicative model contrast measures.
2012/9/19
Images obtained with coherent illumination, as is the case of sonar, ultrasound-B, laser and Synthetic Aperture Radar – SAR, are affected by speckle noise which reduces the ability to extract informat...
Parameter estimation in the stochastic Morris-Lecar neuronal model with particle filter methods
Parameter estimatio stochastic Morris-Lecar neuronal mode particle filter methods
2012/9/19
In this paper, we consider the classic measurement error regression scenario in which our independent,or design, variables are observed with several sources of additive noise. We will show that our mo...
Generalized Interference Models in Doubly Stochastic Poisson Random Fields for Wideband Communications: the PNSC(alpha) model
Interference models Cox Process Doubly Stochastic Poisson Stable Process Isotropicα-stable Complexα-stable
2012/9/19
A general stochastic model is developed for the total interference in wideband systems, denoted as the PNSC(α) Interference Model. It allows one to obtain, analytic representations in situations where...
Asymptotic Normality of Maximum Likelihood and its Variational Approximation for Stochastic Blockmodels
network statistics stochastic blockmodeling, varia-tional methods maximum likelihood
2012/9/18
Variational methods for parameter estimation are an activere-search area, potentially offering computationally tractable heuristics with theoretical performance bounds. We build on recent work that ap...
Stochastic linear programming with a distortion risk constraint
Robust optimization weighted-mean trimmed regions central regions coherent risk measure spectral risk measure mean-risk portfolio.
2012/9/17
Linear optimization problems are investigated whose parametersare uncertain. We apply coherent distortion risk measures to capture the pos-sible violation of a restriction. Each risk constraint induce...
Stochastic Approximation and Newton's Estimate of a Mixing Distribution
Stochastic approximation empirical Bayes mixture models Lyapunov functions
2011/3/23
Many statistical problems involve mixture models and the need for computationally efficient methods to estimate the mixing distribution has increased dramatically in recent years. Newton [Sankhya Ser....
Fast Inference of Interactions in Assemblies of Stochastic Integrate-and-Fire Neurons from Spike Recordings
Bayesian procedures noise variance activity of the salamander
2011/3/24
We present two Bayesian procedures to infer the interactions and external currents in an assembly of stochastic integrate-and-fire neurons from the recording of their spiking activity. The first proce...
Stochastic model selection for Mixtures of Matrix-Normals
Mixture models birth and death process Gibbs sampler
2010/10/19
Finite mixtures of matrix normal distributions are a powerful tool for classifying three-way data in unsupervised problems. The distribution of each component is assumed to be a matrix variate normal ...