nimare.meta.ibma.RFX_GLM¶
-
class
RFX_GLM(null='theoretical', n_iters=None, two_sided=True, *args, **kwargs)[source]¶ A t-test on contrast images. Requires contrast images.
- Parameters
null ({‘theoretical’, ‘empirical’}, optional) – Whether to use a theoretical null T distribution or an empirically- derived null distribution determined via sign flipping. Default is ‘theoretical’.
n_iters (
intorNone, optional) – The number of iterations to run in estimating the null distribution. Only used ifnull = 'empirical'.two_sided (
bool, optional) – Whether to do a two- or one-sided test. Default is True.
-
fit(dataset)[source]¶ Fit Estimator to Dataset.
- Parameters
dataset (
nimare.dataset.Dataset) – Dataset object to analyze.- Returns
nimare.results.MetaResult– Results of Estimator fitting.
Notes
The
fitmethod is a light wrapper that runs input validation and preprocessing before fitting the actual model. Estimators’ individual “fitting” methods are implemented as_fit, although users should callfit.
-
get_params(deep=True)[source]¶ Get parameters for this estimator.
- Parameters
deep (boolean, optional) – If True, will return the parameters for this estimator and contained subobjects that are estimators.
- Returns
params (mapping of string to any) – Parameter names mapped to their values.