Man pages for xnet
Two-Step Kernel Ridge Regression for Network Predictions
| as_tuned | convert tskrr models |
| create_grid | Create a grid of values for tuning tskrr |
| dim-tskrr-method | Get the dimensions of a tskrr object |
| drugTargetInteraction | drug target interactions for neural receptors |
| eigen2hat | Calculate the hat matrix from an eigen decomposition |
| fitted | extract the predictions |
| get_loo_fun | Retrieve a loo function |
| getters_linearFilter | Getters for linearFilter objects |
| getters-permtest | Getters for permtest objects |
| getters-tskrr | Getters for tskrr objects |
| getters-tskrrImpute | Getters for tskrrImpute objects |
| getters-tskrrTune | Getters for tskrrTune objects |
| hat | Return the hat matrix of a tskrr model |
| impute_tskrr | Impute missing values in a label matrix |
| impute_tskrr.fit | Impute values based on a two-step kernel ridge regression |
| is_symmetric | Test symmetry of a matrix |
| labels | Extract labels from a tskrr object |
| linear_filter | Fit a linear filter over a label matrix |
| linearFilter-class | Class linearFilter |
| loo | Leave-one-out cross-validation for tskrr |
| looInternal | Leave-one-out cross-validation for two-step kernel ridge... |
| loss | Calculate or extract the loss of a tskrr model |
| loss_functions | loss functions |
| match_labels | Reorder the label matrix |
| permtest | Calculate the relative importance of the edges |
| permtest-class | Class permtest |
| plot_grid | Plot the grid of a tuned tskrr model |
| plot.tskrr | plot a heatmap of the predictions from a tskrr model |
| predict | predict method for tskrr fits |
| proteinInteraction | Protein interaction for yeast |
| residuals.tskrr | calculate residuals from a tskrr model |
| test_symmetry | test the symmetry of a matrix |
| tskrr | Fitting a two step kernel ridge regression |
| tskrr-class | Class tskrr |
| tskrr.fit | Carry out a two-step kernel ridge regression |
| tskrrHeterogeneous-class | Class tskrrHeterogeneous |
| tskrrHomogeneous-class | Class tskrrHomogeneous |
| tskrrImpute-class | Class tskrrImpute |
| tskrrImputeHeterogeneous-class | Class tskrrImputeHeterogeneous |
| tskrrImputeHomogeneous-class | Class tskrrImputeHomogeneous |
| tskrrTune-class | Class tskrrTune |
| tskrrTuneHeterogeneous-class | Class tskrrTuneHeterogeneous |
| tskrrTuneHomogeneous-class | Class tskrrTuneHomogeneous |
| tune | tune the lambda parameters for a tskrr |
| update | Update a tskrr object with a new lambda |
| valid_dimensions | Functions to check matrices |
| valid_labels | Test the correctness of the labels. |
| weights | Extract weights from a tskrr model |
| xnet-package | Two-step kernel ridge regression for network analysis |
