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xnet (version 0.1.11)

Two-Step Kernel Ridge Regression for Network Predictions

Description

Fit a two-step kernel ridge regression model for predicting edges in networks, and carry out cross-validation using shortcuts for swift and accurate performance assessment (Stock et al, 2018 ).

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Install

install.packages('xnet')

Monthly Downloads

148

Version

0.1.11

License

GPL-3

Issues

2

Pull Requests

0

Stars

11

Forks

2

Maintainer

Joris Meys

Last Published

February 3rd, 2020

Functions in xnet (0.1.11)

as_tuned

convert tskrr models
hat

Return the hat matrix of a tskrr model
match_labels

Reorder the label matrix
tskrrHomogeneous-class

Class tskrrHomogeneous
loss_functions

loss functions
tskrrImpute-class

Class tskrrImpute
impute_tskrr.fit

Impute values based on a two-step kernel ridge regression
impute_tskrr

Impute missing values in a label matrix
permutations

Getters for permtest objects
create_grid

Create a grid of values for tuning tskrr
get_loo_fun

Retrieve a loo function
is_symmetric

Test symmetry of a matrix
response,tskrr-method

Getters for tskrr objects
permtest-class

Class permtest
update

Update a tskrr object with a new lambda
tskrrImputeHeterogeneous-class

Class tskrrImputeHeterogeneous
valid_dimensions

Functions to check matrices
permtest

Calculate the relative importance of the edges
tskrrImputeHomogeneous-class

Class tskrrImputeHomogeneous
eigen2hat

Calculate the hat matrix from an eigen decomposition
loss

Calculate or extract the loss of a tskrr model
alpha

Getters for linearFilter objects
drugTargetInteraction

drug target interactions for neural receptors
dim,tskrr-method

Get the dimensions of a tskrr object
is_tuned

Getters for tskrrTune objects
loo_internal

Leave-one-out cross-validation for two-step kernel ridge regression
fitted.tskrr

extract the predictions
linear_filter

Fit a linear filter over a label matrix
tskrrTuneHomogeneous-class

Class tskrrTuneHomogeneous
plot.tskrr

plot a heatmap of the predictions from a tskrr model
tskrr.fit

Carry out a two-step kernel ridge regression
labels.tskrr

Extract labels from a tskrr object
linearFilter-class

Class linearFilter
plot_grid

Plot the grid of a tuned tskrr model
has_imputed_values

Getters for tskrrImpute objects
tskrrHeterogeneous-class

Class tskrrHeterogeneous
tune

tune the lambda parameters for a tskrr
loo

Leave-one-out cross-validation for tskrr
predict.tskrr

predict method for tskrr fits
proteinInteraction

Protein interaction for yeast
tskrrTuneHeterogeneous-class

Class tskrrTuneHeterogeneous
tskrr

Fitting a two step kernel ridge regression
tskrr-class

Class tskrr
xnet-package

Two-step kernel ridge regression for network analysis
tskrrTune-class

Class tskrrTune
residuals

calculate residuals from a tskrr model
test_symmetry

test the symmetry of a matrix
valid_labels

Test the correctness of the labels.
weights,tskrrHeterogeneous-method

Extract weights from a tskrr model