Springer Texts in Statistics - A First Course in Bayesian Statistical Methods
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Published By Springer New York

9780387922997, 9780387924076

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One-parameter models

Springer Texts in Statistics - A First Course in Bayesian Statistical Methods ◽

10.1007/978-0-387-92407-6_3 ◽

2009 ◽

pp. 31-52 ◽

Cited By ~ 1

Author(s):

Peter D. Hoff

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Posterior approximation with the Gibbs sampler

Springer Texts in Statistics - A First Course in Bayesian Statistical Methods ◽

10.1007/978-0-387-92407-6_6 ◽

2009 ◽

pp. 89-104

Author(s):

Peter D. Hoff

Keyword(s):

Gibbs Sampler ◽

Posterior Approximation

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The normal model

Springer Texts in Statistics - A First Course in Bayesian Statistical Methods ◽

10.1007/978-0-387-92407-6_5 ◽

2009 ◽

pp. 67-87 ◽

Cited By ~ 1

Author(s):

Peter D. Hoff

Keyword(s):

Normal Model

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Belief, probability and exchangeability

Springer Texts in Statistics - A First Course in Bayesian Statistical Methods ◽

10.1007/978-0-387-92407-6_2 ◽

2009 ◽

pp. 13-30

Author(s):

Peter D. Hoff

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Linear and generalized linear mixed effects models

Springer Texts in Statistics - A First Course in Bayesian Statistical Methods ◽

10.1007/978-0-387-92407-6_11 ◽

2009 ◽

pp. 195-207 ◽

Cited By ~ 2

Author(s):

Peter D. Hoff

Keyword(s):

Mixed Effects ◽

Mixed Effects Models ◽

Linear Mixed Effects Models ◽

Linear Mixed Effects ◽

Generalized Linear Mixed Effects

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Linear regression

Springer Texts in Statistics - A First Course in Bayesian Statistical Methods ◽

10.1007/978-0-387-92407-6_9 ◽

2009 ◽

pp. 149-170 ◽

Cited By ~ 1

Author(s):

Peter D. Hoff

Keyword(s):

Linear Regression

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Nonconjugate priors and Metropolis-Hastings algorithms

Springer Texts in Statistics - A First Course in Bayesian Statistical Methods ◽

10.1007/978-0-387-92407-6_10 ◽

2009 ◽

pp. 171-193 ◽

Cited By ~ 1

Author(s):

Peter D. Hoff

Keyword(s):

Metropolis Hastings Algorithms

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The multivariate normal model

Springer Texts in Statistics - A First Course in Bayesian Statistical Methods ◽

10.1007/978-0-387-92407-6_7 ◽

2009 ◽

pp. 105-123

Author(s):

Peter D. Hoff

Keyword(s):

Normal Model ◽

Multivariate Normal ◽

Multivariate Normal Model

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Latent variable methods for ordinal data

Springer Texts in Statistics - A First Course in Bayesian Statistical Methods ◽

10.1007/978-0-387-92407-6_12 ◽

2009 ◽

pp. 209-223

Author(s):

Peter D. Hoff

Keyword(s):

Latent Variable ◽

Ordinal Data ◽

Latent Variable Methods

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Monte Carlo approximation

Springer Texts in Statistics - A First Course in Bayesian Statistical Methods ◽

10.1007/978-0-387-92407-6_4 ◽

2009 ◽

pp. 53-65

Author(s):

Peter D. Hoff

Keyword(s):

Monte Carlo ◽

Monte Carlo Approximation

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Springer Texts in Statistics - A First Course in Bayesian Statistical MethodsLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer New York

One-parameter models

Posterior approximation with the Gibbs sampler

The normal model

Belief, probability and exchangeability

Linear and generalized linear mixed effects models

Linear regression

Nonconjugate priors and Metropolis-Hastings algorithms

The multivariate normal model

Latent variable methods for ordinal data

Monte Carlo approximation

Springer Texts in Statistics - A First Course in Bayesian Statistical Methods
Latest Publications