Sampling from multivariate correlated binary and poisson random variables: binHist(S) - File Exchange

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Sampling from multivariate correlated binary and poisson random variables

DGAnyMarginal(pmfs,Sigma,supp... [samples,gammas,Lambda,joints2D,hists] = DGAnyMarginal(pmfs,Sigma,supports,Nsamples)
EstimateDiscreteJoint(A) [B,ranges] = EstimateDiscreteJoint(A)
PoissonMarginals(means,acc) % [pmfs,supports] = PoissonMarginals(means,acc)
SampleDGAnyMarginal(gammas,La... [samples,hists]=SampleDGAnyMarginal(gammas,Lambda,supports,Nsamples)
[gammas,Lambda,joints2D]=Find... % [gammas,Lambda,joints2D] = FindDGAnyMarginal(pmfs,Sigma,supports)
[samples,gammas,Lambda,joints... [samples,gammas,Lambda,joints2D,cmfs,hists] = DGPoisson(means,Sigma,Nsamples,acc)
[y]=bivnor(a,b,rho)
binBinaryToDec(bin) dec = binBinaryToDec(bin)
binHist(S)
binHistIndep(mu) hc = binHistIndep(mu)
countElem(x,sv,ev)
findLatentGaussian(m,c,acc)
sampleCovPoisson(m,C,nSamples... x = sampleCovPoisson(m,C,nSamples,err)
sampleDichGauss01(mu,Sigma,ns... [s gamma rho] = sampleDichGauss01(mu,Sigma,nsamples,already_computed,acc)
vec(v)
demo.m
setPath.m
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from Sampling from multivariate correlated binary and poisson random variables by Philipp Berens
These Matlab functions can be used to generate multivariate correlated binary variables, and correl

binHist(S)

function hc = binHist(S)
% hc = binHist(S)
%   Generates histogram for binary vectors in S
%   S = D * N matrix
%
% Code from the paper: 'Generating spike-trains with specified
% correlations', Macke et al., submitted to Neural Computation
%
% www.kyb.mpg.de/bethgegroup/code/efficientsampling


D = size(S,1);
C = binBinaryToDec(S);
hc = countElem(C,0,2^D);

Highlights from Sampling from multivariate correlated binary and poisson random variables

Highlights from
Sampling from multivariate correlated binary and poisson random variables