| multiview-package | Cooperative learning for multiple views using generalized linear models |
| coef.cv.multiview | Extract coefficients from a cv.multiview object |
| coef.multiview | Extract coefficients from a multiview object |
| coef_ordered | Extract an ordered list of standardized coefficients from a 'multiview' or 'cv.multiview' object |
| coef_ordered.cv.multiview | Extract an ordered list of standardized coefficients from a cv.multiview object |
| coef_ordered.multiview | Extract an ordered list of standardized coefficients from a multiview object |
| collapse_named_lists | Collapse a list of named lists into one list with the same name |
| cox_obj_function | Elastic net objective function value for Cox regression model |
| cv.multiview | Perform k-fold cross-validation for cooperative learning |
| dev_function | Elastic net deviance value |
| elnet.fit | Solve weighted least squares (WLS) problem for a single lambda value |
| get_cox_lambda_max | Get lambda max for Cox regression model |
| get_eta | Helper function to get etas (linear predictions) |
| get_start | Get null deviance, starting mu and lambda max |
| make_row | Build a block row matrix for multiview |
| multiview | Perform cooperative learning using the direct algorithm for two or more views. |
| multiview.control | Internal multiview parameters |
| multiview.cox.fit | Fit a Cox regression model with elastic net regularization for a single value of lambda |
| multiview.cox.path | Fit a Cox regression model with elastic net regularization for a path of lambda values |
| multiview.fit | Fit a GLM with elastic net regularization for a single value of lambda |
| multiview.path | Fit a GLM with elastic net regularization for a path of lambda values |
| obj_function | Elastic net objective function value |
| pen_function | Elastic net penalty value |
| plot.multiview | Plot coefficients from a "multiview" object |
| predict.cv.multiview | Make predictions from a "cv.multiview" object. |
| predict.multiview | Get predictions from a 'multiview' fit object |
| reshape_x_to_xlist | Return a new list of x matrices of same shapes as those in x_list |
| response.coxnet | Make response for coxnet |
| select_matrix_list_columns | Select x_list columns specified by (conformable) list of indices |
| to_nvar_index | Translate from column indices in list of x matrices to indices in '1:nvars'. No sanity checks for efficiency |
| to_xlist_index | Translate indices in '1:nvars' to column indices in list of x matrices. No sanity checks |
| view.contribution | Evaluate the contribution of data views in making prediction |
| weighted_mean_sd | Helper function to compute weighted mean and standard deviation |