<--- Back to Details
First PageDocument Content
Statistical inference / Computational statistics / Markov models / Bayesian statistics / Estimation theory / Markov chain Monte Carlo / Mixture model / Bayesian inference / Particle filter / Statistics / Probability and statistics / Monte Carlo methods
Date: 2011-08-09 11:47:34
Statistical inference
Computational statistics
Markov models
Bayesian statistics
Estimation theory
Markov chain Monte Carlo
Mixture model
Bayesian inference
Particle filter
Statistics
Probability and statistics
Monte Carlo methods

Bayesian Analysis and Computational Methods for Dynamic Modeling

Add to Reading List

Source URL: niemiconsulting.com

Download Document from Source Website

File Size: 2,86 MB

Share Document on Facebook

Similar Documents

Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes Nima Anari ∗

DocID: 1vbSk - View Document

Compiling Markov Chain Monte Carlo Algorithms for Probabilistic Modeling Daniel Huang Jean-Baptiste Tristan

DocID: 1uvqp - View Document

Appendix 3 Markov Chain Monte Carlo and Gibbs Sampling A constant them in the development of statistics has been the search for justifications for what statisticians do — BlascoDraft version 12 September 2008

DocID: 1urnq - View Document

Compiling Markov Chain Monte Carlo Algorithms for Probabilistic Modeling Daniel Huang Jean-Baptiste Tristan

DocID: 1uaEC - View Document

Appendix 3 Markov Chain Monte Carlo and Gibbs Sampling Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise – Tukey

DocID: 1u5jA - View Document