| 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 |