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xnet  

Two-Step Kernel Ridge Regression for Network Predictions
View on CRAN: Click here


Download and install xnet package within the R console
Install from CRAN:
install.packages("xnet")

Install from Github:
library("remotes")
install_github("cran/xnet")

Install by package version:
library("remotes")
install_version("xnet", "0.1.11")



Attach the package and use:
library("xnet")
Maintained by
Joris Meys
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-01-09
Latest Update: 2020-02-03
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 <doi:10.1093/bib/bby095> ).
How to cite:
Joris Meys (2020). xnet: Two-Step Kernel Ridge Regression for Network Predictions. R package version 0.1.11, https://cran.r-project.org/web/packages/xnet
Previous versions and publish date:
0.1.10 (2020-01-09 10:30)
Other packages that cited xnet R package
View xnet citation profile
Other R packages that xnet depends, imports, suggests or enhances
Functions, R codes and Examples using the xnet R package
Some associated functions: as_tuned . create_grid . dim-tskrr-method . drugTargetInteraction . eigen2hat . fitted . get_loo_fun . getters-permtest . getters-tskrr . getters-tskrrImpute . getters-tskrrTune . getters_linearFilter . hat . impute_tskrr.fit . impute_tskrr . is_symmetric . labels . linearFilter-class . linear_filter . loo . looInternal . loss . loss_functions . match_labels . permtest-class . permtest . plot.tskrr . plot_grid . predict . proteinInteraction . residuals.tskrr . test_symmetry . tskrr-class . tskrr.fit . tskrr . tskrrHeterogeneous-class . tskrrHomogeneous-class . tskrrImpute-class . tskrrImputeHeterogeneous-class . tskrrImputeHomogeneous-class . tskrrTune-class . tskrrTuneHeterogeneous-class . tskrrTuneHomogeneous-class . tune . update . valid_dimensions . valid_labels . weights . xnet-package . 
Some associated R codes: Class_linearFilter.R . Class_permtest.R . Class_tskrr.R . Class_tskrrHeterogeneous.R . Class_tskrrHomogeneous.R . Class_tskrrImpute.R . Class_tskrrImputeHeterogeneous.R . Class_tskrrImputeHomogeneous.R . Class_tskrrTune.R . Class_tskrrTuneHeterogeneous.R . Class_tskrrTuneHomogeneous.R . all_generics.R . as_tuned.R . create_grid.R . data_drugtarget.R . data_proteinInteraction.R . dim.R . eigen2hat.R . fitted.R . get_loo_fun.R . getlooInternal.R . getters_linearFilter.R . getters_permtest.R . getters_tskrr.R . getters_tskrrImpute.R . getters_tskrrTune.R . hat.R . impute_tskrr.R . impute_tskrr.fit.R . internal_helpers.R . is_symmetric.R . labels.R . linear_filter.R . loo.R . looInternal.R . loss.R . loss_functions.R . match_labels.R . permtest.R . plot.tskrr.R . plot_grid.R . predict.R . prepare_lambdas.R . residuals.R . test_input.R . test_symmetry.R . tskrr.R . tskrr.fit.R . tune.R . update.R . valid_dimensions.R . valid_labels.R . weights.R . xnet-package.R .  Full xnet package functions and examples
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