AP Statistics Curriculum 2007 Bayesian Gibbs

From SOCR
Jump to: navigation, search

Probability and Statistics Ebook - Expectation Maximization Estimation, Gibbs Sampling and Monte Carlo Simulations

Gibbs sampling is an algorithm to generate a sequence of samples from the joint probability distribution of two or more random variables. The purpose of this sequence is to approximate the joint distribution, or to compute an expected value. Gibbs sampling is a special case of the Metropolis-Hastings algorithm and is also an example of a Markov chain Monte Carlo algorithm.

Introduction to numerical methods

EM algorithm

Data augmentation by Monte Carlo

The Gibbs Sampler

Rejection Sampling

Metropolis Hastings Algorithm

Generalized Linear Model

See also

References




Translate this page:

(default)
Uk flag.gif

Deutsch
De flag.gif

Español
Es flag.gif

Français
Fr flag.gif

Italiano
It flag.gif

Português
Pt flag.gif

日本語
Jp flag.gif

България
Bg flag.gif

الامارات العربية المتحدة
Ae flag.gif

Suomi
Fi flag.gif

इस भाषा में
In flag.gif

Norge
No flag.png

한국어
Kr flag.gif

中文
Cn flag.gif

繁体中文
Cn flag.gif

Русский
Ru flag.gif

Nederlands
Nl flag.gif

Ελληνικά
Gr flag.gif

Hrvatska
Hr flag.gif

Česká republika
Cz flag.gif

Danmark
Dk flag.gif

Polska
Pl flag.png

România
Ro flag.png

Sverige
Se flag.gif