| Multivariate Pattern Analysis in Python

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This content refers to the previous stable release of PyMVPA. Please visit www.pymvpa.org for the most recent version of PyMVPA and its documentation.

# misc.stats

## Module: `misc.stats`

Inheritance diagram for `mvpa.misc.stats`:

Little statistics helper

## `DSMatrix`

class `mvpa.misc.stats.``DSMatrix`(data_vectors, metric='spearman')

  Bases: `object`

  DSMatrix allows for the creation of dissilimarity matrices using arbitrary distance metrics.

  Initialize DSMatrix

  Parameters:

  - data_vectors (ndarray) – m x n collection of vectors, where m is the number of exemplars and n is the number of features per exemplar
  - metric (string) – Distance metric to use (e.g., ‘euclidean’, ‘spearman’, ‘pearson’, ‘confusion’)

  `getFullMatrix`()
  `getMetric`()
  `getTriangle`()
  `getVectorForm`()

`mvpa.misc.stats.``chisquare`(obs, exp=None)

  Compute the chisquare value of a contingency table with arbitrary dimensions.

  If no expected frequencies are supplied, the total N is assumed to be equally distributed across all cells.

  Returns: chisquare-stats, associated p-value (upper tail)

### Navigation

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