Statistics#

Functions for statistical analysis.

Parametric statistics (see scipy.stats and statsmodels for more options):

`ttest_1samp_no_p`(X[, sigma, method])	Perform one-sample t-test.
`ttest_ind_no_p`(a, b[, equal_var, sigma])	Independent samples t-test without p calculation.
`f_oneway`(*args)	Perform a 1-way ANOVA.
`f_mway_rm`(data, factor_levels[, effects, ...])	Compute M-way repeated measures ANOVA for fully balanced designs.
`f_threshold_mway_rm`(n_subjects, factor_levels)	Compute F-value thresholds for a two-way ANOVA.
`linear_regression`(inst, design_matrix[, names])	Fit Ordinary Least Squares (OLS) regression.
`linear_regression_raw`(raw, events[, ...])	Estimate regression-based evoked potentials/fields by linear modeling.

Mass-univariate multiple comparison correction:

`bonferroni_correction`(pval[, alpha])	P-value correction with Bonferroni method.
`fdr_correction`(pvals[, alpha, method])	P-value correction with False Discovery Rate (FDR).

Non-parametric (clustering) resampling methods:

`combine_adjacency`(*structure)	Create a sparse binary adjacency/neighbors matrix.
`permutation_cluster_test`(X[, threshold, ...])	Cluster-level statistical permutation test.
`permutation_cluster_1samp_test`(X[, ...])	Non-parametric cluster-level paired t-test.
`permutation_t_test`(X[, n_permutations, ...])	One sample/paired sample permutation test based on a t-statistic.
`spatio_temporal_cluster_test`(X[, threshold, ...])	Non-parametric cluster-level test for spatio-temporal data.
`spatio_temporal_cluster_1samp_test`(X[, ...])	Non-parametric cluster-level paired t-test for spatio-temporal data.
`summarize_clusters_stc`(clu[, p_thresh, ...])	Assemble summary SourceEstimate from spatiotemporal cluster results.
`bootstrap_confidence_interval`(arr[, ci, ...])	Get confidence intervals from non-parametric bootstrap.

Compute adjacency matrices for cluster-level statistics:

`channels.find_ch_adjacency`(info, ch_type)	Find the adjacency matrix for the given channels.
`channels.read_ch_adjacency`(fname[, picks])	Read a channel adjacency ("neighbors") file that ships with MNE.
`spatial_dist_adjacency`(src, dist[, verbose])	Compute adjacency from distances in a source space.
`spatial_src_adjacency`(src[, dist, verbose])	Compute adjacency for a source space activation.
`spatial_tris_adjacency`(tris[, ...])	Compute adjacency from triangles.
`spatial_inter_hemi_adjacency`(src, dist[, ...])	Get vertices on each hemisphere that are close to the other hemisphere.
`spatio_temporal_src_adjacency`(src, n_times)	Compute adjacency for a source space activation over time.
`spatio_temporal_tris_adjacency`(tris, n_times)	Compute adjacency from triangles and time instants.
`spatio_temporal_dist_adjacency`(src, n_times, ...)	Compute adjacency from distances in a source space and time instants.