Software für MatLab und Python

CircStat

A toolbox for circular or direction statistics, containg a wide selection of descriptive techniques for such data, as well as inferential methods ranging from simple tests for uniformity to complex to factor ANOVA like tests. It has been descriped in the paper

Berens, P.: CircStat: A MATLAB Toolbox for Circular Statistics , Journal of Statistical Software, 2009
From the journal website, a tutorial can be downloaded.From the journal website, a tutorial can be downloaded.

MVD

A toolbox to efficiently sample from (1) correlated multivariate binary random variables (multivariate Bernoulli), (2) correlated multivariate Poisson random variables and (3) correlated random variables with arbitrary marginal statistics. Applications include modeling and generating of artificial neural data. It is based on the methods i

Macke, J. H., P. Berens, A. S. Ecker, A. S. Tolias and M. Bethge: Generating Spike Trains with Specified Correlation Coefficients , Neural Computation, 2009
The file also contains a tutorial to reproduce most figures from the paper. The file also contains a tutorial to reproduce most figures from the paper.

NISDET - A Natural Image Statistics Density Estimation Toolbox

The toolbox includes code for fitting Lp-spherically symmetric distributions as described in
Sinz, F. and M. Bethge: The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction., NIPS, 2009

It also includes code for fitting the quantitative ICA (QICA) as described in
Eichhorn, J., F. H. Sinz and M. Bethge: Natural Image Coding in V1: How Much Use is Orientation Selectivity? , PLOS Computational Biology, 2009

Furthermore, it provides code for Lp-nested symmetric distributions as described in
Sinz, F., E. P. Simoncelli and M. Bethge: Hierarchical Modeling of Local Image Features through Lp-Nested Symmetric Distributions., NIPS, 2010

In addition, it implements several whitening routines and allows for optimizing filter on the log-likelihood of the aforementioned models. A quick tutorial is provided explaining the usage of the toolbox. In addition, it implements several whitening routines and allows for optimizing filter on the log-likelihood of the aforementioned models. A quick tutorial is provided explaining the usage of the toolbox.

NATTER - A Natural Image Statistics Density Estimation Toolbox for Python

The toolbox is an advancement of the NISDET toolbox. It includes more distributions, more functionality. In particular, it includes more functionality for Lp-nested symmetric distributions. It also includes the algorithms for radial factorization and nested radial factorization.