Two-Step Kernel Ridge Regression for Network Predictions

Vignettes

- Package overview
- A short introduction to cross-network analysis with xnet"
- Preparation of the example data"
- S4 class structure of the xnet package"

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**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**Browse all...**

The class tskrrTuneHeterogeneous represents a tuned Heterogeneous
`tskrr`

model. It inherits from
the classes `tskrrHeterogeneous`

and `tskrrTune`

.

xnet documentation built on Feb. 4, 2020, 9:10 a.m.

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