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Highlights from
mcmc
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betalpr(p1,p2,alpha,beta)
BETALPR - Beta Distribution - Log Probability Ratio
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gamlpr(g1, g2, alph, gam)
GAMLPR = Gamma Distribution - Log Probability Density Ratio
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invwishirnd(S,d)
INVWISHIRND - Inverse Wishart Random Matrix
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invwishlpr(IW1, IW2, S, d)
INVWISHLPR = Inverse Wishart Distribution - Log Probability Density Ratio
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invwishpdf(IW,S,d)
INVWISHPDF = Inverse Wishart Distribution - Probability Density Function
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invwishrnd(S,d)
INVWISHRND - Inverse Wishart Distribution - Random Matrix Value
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ltindex(index, dim) ;
LTINDEX - Lower Triangular Index
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ltvec(m)
LTVEC - Change a Lower-Triangular Matrix into a Vector
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ltvec(v)
VECLT - change a vector into a lower-triangular matrix
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mcmcgr(A,ng) ;
MCMCGR - Gelman-Rubin R statistic for convergence
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mcmclt(A)
MCMLT - makes matrix of MCMC runs lower triangular
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mcmcsumm(A)
MCMCSUMM - Summary Statistics
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mcmctrace(A)
MCMCTRACE - trace plots
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metrop ( logq, newval, oldval...
METROP - perform a Metropolis-Hastings step
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mvnormlpr (x1, x2, mu, sigma)
MVNORMLPR - Multivariate Normal Distribution - Log Density Ratio
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mvnormrnd (mu,sigma,n)
MVNORMRND - Multivariate Normal - Random Number Generation
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wishirnd(Sc,n)
WISHIRND - Wishart Distribution - Random Matrix
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wishrnd(Sc,nu)
WISHRND - Random Matrix from Wishart Distribution
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Contents.m
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mcmcacf.m
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mcmcdemo.m
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randrand.m
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About_MCMC.html
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index.html
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View all files
from
mcmc
by David Shera
MCMC -- Markov Chain Monte Carlo Tools
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| invwishrnd(S,d) |
% INVWISHRND - Inverse Wishart Distribution - Random Matrix Value
% Copyright (c) 1998, Harvard University. Full copyright in the file Copyright
%
% [ IW ] = invwishrnd(S,d)
%
% S = p x p symmetric, postitive definite "scale" matrix
% d = "degrees of freedom" parameter (integer)
% = "precision" parameter (d may be non-integer)
%
% IW = random matrix from the inverse Wishart distribution
%
% Note:
% Different sources use different parameterizations.
% This routine uses that of Press and Shigemasu (1989):
% density (IW) is proportional to
% exp[-.5*trace(S*inv(IW))] / [det(IW) ^ (d/2)].
%
% With this density definition:
% mean of IW = S/(d-2p-2) for d>2p+2,
% mode of IW = S/d.
%
% See also: INVWISHIRND, WISHRND
function [IW] = invwishrnd(S,d)
[p,p2] = size(S) ;
W = wishrnd(inv(S),d-p-1) ;
IW = inv(W) ;
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