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Journal of the American Statistical Association Volume 85, 1990 - Issue 410
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Theory and Methods

Sampling-Based Approaches to Calculating Marginal Densities

Alan E. Gelfand Department of Statistics, University of Connecticut, Storrs, CT, 06269-3120
&
Adrian F. M. Smith Department of Mathematics, Imperial College of Science, Technology, and Medicine, University of London, London, SW7 2AZ, England
Pages 398-409 | Received 01 Nov 1988, Published online: 28 Feb 2012
 
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Abstract

Stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm can be viewed as three alternative sampling- (or Monte Carlo-) based approaches to the calculation of numerical estimates of marginal probability distributions. The three approaches will be reviewed, compared, and contrasted in relation to various joint probability structures frequently encountered in applications. In particular, the relevance of the approaches to calculating Bayesian posterior densities for a variety of structured models will be discussed and illustrated.

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Bayesian detection of potential risk using inference on blinded safety data.
Source: Wiley
Choice models for predicting divisional winners in major league baseball
Source: Informa UK Limited
Bayesian Estimation and Model Choice in Item Response Models
Source: Informa UK Limited
Posterior Computations for Censored Regression Data
Source: Informa UK Limited
Impact of statistical adjustment for frequency of venue attendance in a venue-based survey of men who have sex with men.
Source: Oxford University Press (OUP)
Behavior of the Gibbs Sampler When Conditional Distributions Are Potentially Incompatible.
Source: Informa UK Limited
Gibbs Sampling
Source: Informa UK Limited
Statistics: a data science for the 21st century
Source: Wiley
Conditional Heteroscedasticity in Qualitative Response Models of Time Series: A Gibbs-Sampling Approach to the Bank Prime Rate
Source: JSTOR
Multiple membership multiple classification (MMMC) models
Source: SAGE Publications
Hierarchical Models and More on Convergence Assessment
Source: Springer New York
HOW MANY COUNTRIES?
Source: Wiley
Hydraulic time constants for transpiration of loblolly pine at a free-air carbon dioxide enrichment site.
Source: Oxford University Press (OUP)
Genetic parameters and direct, maternal and heterosis effects on litter size in a diallel cross among three commercial varieties of Iberian pig
Source: Cambridge University Press (CUP)
Transmission of macroeconomic shocks to risk parameters: Their uses in stress testing
Source: Wiley
Conditionally Gaussian Random Sequences for an Integrated Variance Estimator with Correlation between Noise and Returns
Source: Wiley
Risk and the Value of Bt Corn
Source: Wiley
FIRM HETEROGENEITY, PERSISTENT AND TRANSIENT TECHNICAL INEFFICIENCY
Source: Wiley
Bayesian Geostatistical Modeling of Malaria Indicator Survey Data in Angola
Source: Public Library of Science (PLoS)
Accounting for Response Misclassification and Covariate Measurement Error Using a Random Effects Logit Model
Source: Informa UK Limited
Bayesian wavelet de-noising with the caravan prior
Source: EDP Sciences
Synthetic protein alignments by CCMgen quantify noise in residue-residue contact prediction
Source: Cold Spring Harbor Laboratory
Ensemble Kalman methods for high-dimensional hierarchical dynamic space-time models
Source: arXiv
Computing bounds on expectations
Source: Informa UK Limited

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