mvpa2.misc.transformers.DistPValue¶
- class mvpa2.misc.transformers.DistPValue(sd=0, distribution='rdist', fpp=None, nbins=400, **kwargs)¶
Converts values into p-values under vague and non-scientific assumptions
Notes
Available conditional attributes:
- nulldist_number+: Number of features within the estimated null-distribution
- positives_recovered+: Number of features considered to be positives and which were recovered
(Conditional attributes enabled by default suffixed with +)
L2-Norm the values, convert them to p-values of a given distribution.
Parameters : sd : int
Samples dimension (if len(x.shape)>1) on which to operate
distribution : string
Which distribution to use. Known are: ‘rdist’ (later normal should be there as well)
fpp : float
At what p-value (both tails) if not None, to control for false positives. It would iteratively prune the tails (tentative real positives) until empirical p-value becomes less or equal to numerical.
nbins : int
Number of bins for the iterative pruning of positives
enable_ca : None or list of str
Names of the conditional attributes which should be enabled in addition to the default ones
disable_ca : None or list of str
Names of the conditional attributes which should be disabled
descr : str
Description of the instance
WARNING: Highly experimental/slow/etc: no theoretical grounds have been :
presented in any paper, nor proven :
