Markov Chain Monte Carlo sampling of posterior distribution

Version 1.5.0.0 (4,29 KB) von
MCMC sampling of using a cascaded metropolis
Aktualisiert 4. Mai 2015

Lizenz anzeigen

NOTE: I recommend using my new GWMCMC sampler which can also be downloaded from the file exchange: http://www.mathworks.com/matlabcentral/fileexchange/49820-the-mcmc-hammer--gwmcmc
Markov Chain Monte Carlo sampling of posterior distribution

A metropolis sampler
[mmc,logP]=mcmc(initialm,loglikelihood,logmodelprior,stepfunction,mccount,skip)
---------
initialm: starting point fopr random walk
loglikelihood: function handle to likelihood function: logL(m)
logprior: function handle to the log model priori probability: logPapriori(m)
stepfunction: function handle with no inputs which returns a random
step in the random walk. (note stepfunction can also be a
matrix describing the size of a normally distributed
step.)
mccount: How long should the markov chain be?
skip: Thin the chain by only storing every N'th step [default=10]

EXAMPLE USAGE: fit a normal distribution to data
-------------------------------------------
data=randn(100,1)*2+3;
logmodelprior=@(m)0; %use a flat prior.
loglike=@(m)sum(log(normpdf(data,m(1),m(2))));
minit=[0 1];
m=mcmc(minit,loglike,logmodelprior,[.2 .5],10000);
m(1:100,:)=[]; %crop drift
plotmatrix(m);

--- Aslak Grinsted 2010

Zitieren als

Aslak Grinsted (2024). Markov Chain Monte Carlo sampling of posterior distribution (https://www.mathworks.com/matlabcentral/fileexchange/47912-markov-chain-monte-carlo-sampling-of-posterior-distribution), MATLAB Central File Exchange. Abgerufen .

Kompatibilität der MATLAB-Version
Erstellt mit R2010a
Kompatibel mit allen Versionen
Plattform-Kompatibilität
Windows macOS Linux
Quellenangaben

Inspiriert von: Ensemble MCMC sampler

Inspiriert: Ensemble MCMC sampler

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Veröffentlicht Versionshinweise
1.5.0.0

1.4.0.0

1.3.0.0

changed description

1.2.0.0

changed title

1.1.0.0

Bugfix for small values of skip

1.0.0.0