搜索结果: 1-15 共查到“统计学 Bayesian Inference”相关记录24条 . 查询时间(0.046 秒)
Informative Bayesian inference for the skew-normal distribution
Bayesian inference Gibbs sampling Markov Chain Monte Carlo Multivariate skew-normal distribution Stochastic representation of the skew-normal Uni
2013/6/14
Motivated by the analysis of the distribution of university grades, which is usually asymmetric, we discuss two informative priors for the shape parameter of the skew-normal distribution, showing that...
Mean field variational Bayesian inference for support vector machine classification
Approximate Bayesian inference variable selection missing data mixed model Markov chain Monte Carlo
2013/6/14
A mean field variational Bayes approach to support vector machines (SVMs) using the latent variable representation on Polson & Scott (2012) is presented. This representation allows circumvention of ma...
A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation
A Fast Iterative Bayesian Inference Algorithm Sparse Channel Estimation
2013/4/27
In this paper, we present a Bayesian channel estimation algorithm for multicarrier receivers based on pilot symbol observations. The inherent sparse nature of wireless multipath channels is exploited ...
Bayesian inference on dependence in multivariate longitudinal data
Cholesky decomposition covariance matrix moment-matching oxidative stress random effects shrinkage prior.
2012/9/17
In many applications, it is of interest to assess the dependence structure in multivariate longitudinal data. Discovering such dependence is challenging
due to the dimensionality involved. By concate...
Robust Bayesian inference of networks using Dirichlet t-distributions
Bayesian inference Dirichlet process graphical model Markov chain Monte Carlo t-distribution.
2012/9/18
Bayesian graphical modeling provides an appealing way to obtain uncertainty esti-mates when inferring network structures, and much recent progress has been made for Gaussian models. These models have ...
Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference
Machine Learning (stat.ML)
2010/12/17
We propose a novel algorithm to solve the expectation propagation relaxation of Bayesian inference for continuous-variable graphical models. In contrast to most previous algorithms, our method is prov...
Bayesian inference and model choice in a hidden stochastic two-compartment model of hematopoietic stem cell fate decisions
Stochastic two-compartment model hidden Markov models reversible jump MCMC hematopoiesis stem cell asymmetric division
2010/11/8
Despite rapid advances in experimental cell biology, the in vivo behavior of hematopoietic stem cells (HSC) cannot be directly ob-served and measured. Previously we modeled feline hematopoiesis using ...
We introduce an extension of the P\'olya tree approach for constructing distributions on the space of probability measures. By using optional stopping and optional choice of splitting variables, the ...
This chapter provides a overview of Bayesian inference, mostly emphasising that it is a
universal method for summarising uncertainty and making estimates and predictions using
probability statements...
ModernWeb services, such as those at Google, Yahoo!, and Ama-
zon, handle billions of requests per day on clusters of thousands of
computers. Because these services operate under strict performance
...
Bayesian inference for the MAPK/ERK pathway by considering the dependency of the kinetic parameters
MCMC MAPK/ERKpathway diusion approximation data augmentation dependency in diusion matrix
2009/9/22
The MAPK/ERK pathway is one of the major signal transduction systems which regulates the cellular growth control of all eukaryotes like the cell proliferation and the apoptosis. Because of its importa...
Bayesian Inference for Shape Mixtures of Skewed Distributions, with Application to Regression Analysis
Posterior analysis regression model shape parameter skewness symmetry
2009/9/22
We introduce a class of shape mixtures of skewed distributions and
study some of its main properties. We discuss a Bayesian interpretation and some
invariance results of the proposed class. We devel...
Semi-parametric Bayesian Inference for Multi-Season Baseball Data
Dirichlet Process Partial Exchangeability Semiparametric Random Effects
2009/9/22
We analyze complete sequences of successes (hits, walks, and sacrices)
for a group of players from the American and National Leagues, collected over
4 seasons. The goal is to describe how players pe...
Bayesian inference for an extended simple regression measurement error model using skewed priors
Berkson model non-informative prior non-random sample pseudo-Bayes factor regression calibration structural error model Winbugs
2009/9/22
In this paper, we introduce a Bayesian extended regression model
with two-stage priors when the covariate is positive and measured with error.
Connections are made with some results in Arellano-Vall...
When did Bayesian Inference become "Bayesian"?
Bayes' Theorem Classical statistical methods Frequentist methods Neo-Bayesian revival Stigler's Law of Eponymy
2009/9/21
While Bayes theorem has a 250-year history, and the method of in-
verse probability that owed from it dominated statistical thinking into the twen-
tieth century, the adjective Byesian was not part ...