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Dirichlet Posterior Sampling with Truncated Multinomial Likelihoods
Dirichlet Posterior Sampling Multinomial Likelihoods
2012/9/18
This document considers the problem of drawing samples from posterior distributions formed under a Dirichlet prior and a truncated multinomial likelihood, by which we mean a Multi-nomial likelihood fu...
Fast MCMC sampling for Markov jump processes and extensions
Markov jump process uniformization MCMC Gibbs sampler Markov-modulated Poisson process continuous-time Bayesian network
2012/9/17
Markov jump processes (or continuous-time Markov chains) are a simple and important class of continuous-time dynamical systems. In this paper, we tackle the problem of simu-lating from the posterior d...
Guaranteed Conservative Fixed Width Confidence Intervals Via Monte Carlo Sampling
Guaranteed Conservative Fixed Width Confidence Intervals Monte Carlo Sampling
2012/9/17
Monte Carlo methods are used to approximate the means,? of random variablesY, whose distributions are not known explicitly. The key idea is that the
average of a random sample,Y1,...,Yn, tends to 礱sn...
How to sample if you must: on optimal functional sampling
Learning Theory Other Applications.
2012/9/17
We examine a fundamental problem that models various active sampling setups, such as network tomography. We analyze sampling of a multivariate normal distribution with an unknown expectation that need...
Dealing with nonresponse in survey sampling: a latent modeling approach
unit nonresponse item nonresponse latent trait models response propensity non-ignorable nonresponse
2012/9/19
Nonresponse is present in almost all surveys and can severely bias estimates. It is usually distinguished between unit and item nonresponse: in the former, we completely fail to have information from ...
Distribution fitting 12. Sampling distribution of compounds abundance from plant species measured by instrumentation. Application to plants metabolism classification
chemical compounds abundances lognormal distribution
2011/7/6
A series of ten plant species belonging to Magnoliopsida - Dicotyledons class were analyzed in terms of chemical compounds distribution of abundance, starting from the assumption that these distributi...
Essentially ML ASN-Minimax double sampling plans
Acceptance sampling by variables ASN-Minimax double sampling plan
2011/7/6
Subject of this paper is ASN-Minimax (AM) double sampling plans by variables for a normally distributed quality characteristic with unknown standard deviation and two-sided specification limits.
Bootstrap of means under stratified sampling
Cluster sampling bootstrap second-order asymptotic
2009/9/16
In a two-stage cluster sampling procedure, $n$ random populations are drawn independently from independent populations and a sub-sample of observations is taken in each of them. The estimator of the g...
Generalised linear mixed model analysis via sequential Monte Carlo sampling
generalised additive models longitudinal data analysis nonparametric regression sequential Monte Carlo sampler
2009/9/16
We present a sequential Monte Carlo algorithm for the Bayesian analysis of generalised linear mixed models (GLMMs). These models support a variety of interesting regression-type analyses, but performi...
Case-deletion importance sampling estimators: Central limit theorems and related results
Infinite Variance Influence Leverage Marginal Residual Sum of Squares Markov Chain Monte Carlo Model Averaging Moment Index Tail Behavior
2009/9/16
Case-deleted analysis is a popular method for evaluating the influence of a subset of cases on inference. The use of Monte Carlo estimation strategies in complicated Bayesian settings leads naturally ...
Construction of weakly CUD sequences for MCMC sampling
completely uniformly distributed Gibbs sampler equidistribution probit quasi-Monte Carlo
2009/9/16
In Markov chain Monte Carlo (MCMC) sampling considerable thought goes into constructing random transitions. But those transitions are almost always driven by a simulated IID sequence. Recently it has ...