MVD - Sampling from Correlated Multivariate Discrete Random Variables
Description
You can use the software in this package to efficiently sample from- correlated multivariate binary random variables (multivariate Bernoulli),
- correlated multivariate Poisson random variables,
- correlated random variables with arbitrary marginal statistics.
demo.m
script.References
J. Macke,
P. Berens,
A. Ecker,
A. Tolias, and
M. Bethge
Generating Spike Trains with Specified Correlation-Coeffcients
Neural Computation, 2009
#spike train, #correlated poisson, #multivariate poisson, #noise correlations, #discretized gaussian
Code, PDF, BibTex
Generating Spike Trains with Specified Correlation-Coeffcients
Neural Computation, 2009
#spike train, #correlated poisson, #multivariate poisson, #noise correlations, #discretized gaussian
Code, PDF, BibTex
M. Bethge and
P. Berens
Near-Maximum Entropy Models for Binary Neural Representations of Natural Images
Advances in Neural Information Processing Systems 20, 2008
#population coding, #natural image statistics, #maximum entropy
Code, PDF, BibTex
Near-Maximum Entropy Models for Binary Neural Representations of Natural Images
Advances in Neural Information Processing Systems 20, 2008
#population coding, #natural image statistics, #maximum entropy
Code, PDF, BibTex
Files
mackeetal.zip (73.2 kB)This file contains
demo.m
, a script to replicate the main figures of the paper Macke et al. (2009).
It can also be downloaded from MATLAB Central File Exchange.