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neurospin.glm.glm

Module: neurospin.glm.glm

Inheritance diagram for nipy.neurospin.glm.glm:

Classes

contrast

class nipy.neurospin.glm.glm.contrast(dim, type='t', tiny=1e-50, dofmax=10000000000.0)
__init__(dim, type='t', tiny=1e-50, dofmax=10000000000.0)
tiny is a numerical constant for computations.
pvalue(baseline=0.0)
Return a parametric approximation of the p-value associated with the null hypothesis: (H0) ‘contrast equals baseline’
stat(baseline=0.0)
Return the decision statistic associated with the test of the null hypothesis: (H0) ‘contrast equals baseline’
summary()
Return a dictionary containing the estimated contrast effect, the associated ReML-based estimation variance, and the estimated degrees of freedom (variance of the variance).
zscore(baseline=0.0)
Return a parametric approximation of the z-score associated with the null hypothesis: (H0) ‘contrast equals baseline’

glm

class nipy.neurospin.glm.glm.glm(Y=None, X=None, formula=None, axis=0, model='spherical', method=None, niter=2)
__init__(Y=None, X=None, formula=None, axis=0, model='spherical', method=None, niter=2)
contrast(c, type='t', tiny=1e-50, dofmax=10000000000.0)
fit(Y, X, formula=None, axis=0, model='spherical', method=None, niter=2)
save(file)

Functions

nipy.neurospin.glm.glm.load(file)
Load a fitted glm
nipy.neurospin.glm.glm.ols(Y, X, axis=0)
Essentially, compute pinv(X)*Y