glm
glm(dm, design, nuisance=None, contrasts=None, return_r2=False)General linear model.
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
| dm | (array, shape(n_samples, n_features)) | Data matrix. | required |
| design | (array, shape(n_samples, n_design_regressors)) | Experimental design regressors. | required |
| nuisance | (array, shape(n_samples, n_nuisance_regressors)) | Nuisance regressors. | None |
| contrasts | (array, shape(n_contrasts, n_design_regressors)) | Contrasts. If None, identity matrix is used, which models the response to each design regressor separately. | None |
Returns
| Name | Type | Description |
|---|---|---|
| betas | (array, shape(n_contrasts, n_features)) | Estimated beta coefficients. |
| ts | (array, shape(n_contrasts, n_features)) | Estimated t-statistics. |
| R2s | (array, shape(n_features)) | Adjusted R-squared values. Only returned if return_r2 is True. |