mvpa.clfs.stats.Nonparametric

Class Nonparametric

Non-parametric 1d distribution -- derives cdf based on stored values.

Introduced to complement parametric distributions present in scipy.stats.

Instance Methods

[hide private]

__init__(self, dist_samples, correction='clip')
x.__init__(...) initializes x; see help(type(x)) for signature

source code

__repr__(self)
repr(x)

source code

cdf(self, x)
Returns the cdf value at x. source code

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __setattr__, __sizeof__, __str__, __subclasshook__

Static Methods

[hide private]

fit(dist_samples)

source code

Properties

[hide private]

Inherited from object: __class__

init(self, dist_samples, correction='clip')
(Constructor)

source code

x.__init__(...) initializes x; see help(type(x)) for signature

Parameters:

dist_samples (ndarray) - Samples to be used to assess the distribution.
correction ({'clip'} or None, optional) - Determines the behavior when .cdf is queried. If None -- no correction is made. If 'clip' -- values are clipped to lie in the range [1/(N+2), (N+1)/(N+2)] (simply because non-parametric assessment lacks the power to resolve with higher precision in the tails, so 'imagery' samples are placed in each of the two tails).

Overrides: object.__init__

repr(self)
(Representation operator)

source code

repr(x)

Overrides: object.__repr__: (inherited documentation)

Class Nonparametric

__init__(self, dist_samples, correction='clip') (Constructor)

__repr__(self) (Representation operator)

init(self, dist_samples, correction='clip')
(Constructor)

repr(self)
(Representation operator)