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vimp  

Perform Inference on Algorithm-Agnostic Variable Importance
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("vimp", "2.3.3")



Attach the package and use:
library("vimp")
Maintained by
Brian D. Williamson
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-06-24
Latest Update: 2023-08-28
Description:
Calculate point estimates of and valid confidence intervals for nonparametric, algorithm-agnostic variable importance measures in high and low dimensions, using flexible estimators of the underlying regression functions. For more information about the methods, please see Williamson et al. (Biometrics, 2020),Williamson et al. (JASA, 2021), and Williamson and Feng (ICML, 2020).
How to cite:
Brian D. Williamson (2018). vimp: Perform Inference on Algorithm-Agnostic Variable Importance. R package version 2.3.3, https://cran.r-project.org/web/packages/vimp. Accessed 07 Nov. 2024.
Previous versions and publish date:
1.0.0 (2018-06-24 13:15), 1.1.0 (2018-08-10 01:00), 1.1.2 (2018-09-21 00:20), 1.1.3 (2018-10-02 21:20), 1.1.4 (2018-10-14 17:40), 1.1.5 (2019-08-10 00:10), 1.1.6 (2019-08-27 00:30), 2.0.1 (2020-04-12 00:50), 2.0.2 (2020-04-27 16:10), 2.1.0 (2020-06-18 20:20), 2.1.6 (2021-01-09 03:20), 2.1.9 (2021-03-01 22:50), 2.2.1 (2021-06-03 18:50), 2.2.2 (2021-06-14 15:50), 2.2.3 (2021-07-20 06:50), 2.2.4 (2021-08-04 06:20), 2.2.5 (2021-08-16 18:30), 2.3.0 (2022-11-14 09:30), 2.3.1 (2022-12-09 18:10)
Other packages that cited vimp R package
View vimp citation profile
Other R packages that vimp depends, imports, suggests or enhances
Complete documentation for vimp
Functions, R codes and Examples using the vimp R package
Some associated functions: average_vim . bootstrap_se . check_fitted_values . check_inputs . create_z . cv_vim . est_predictiveness . est_predictiveness_cv . estimate . estimate.predictiveness_measure . estimate_eif_projection . estimate_nuisances . estimate_type_predictiveness . extract_sampled_split_predictions . format.predictiveness_measure . format.vim . get_cv_sl_folds . get_full_type . get_test_set . make_folds . make_kfold . measure_accuracy . measure_anova . measure_auc . measure_average_value . measure_cross_entropy . measure_deviance . measure_mse . measure_r_squared . merge_vim . predictiveness_measure . print.predictiveness_measure . print.vim . process_arg_lst . run_sl . sample_subsets . scale_est . sp_vim . spvim_ics . spvim_se . vim . vimp . vimp_accuracy . vimp_anova . vimp_auc . vimp_ci . vimp_deviance . vimp_hypothesis_test . vimp_regression . vimp_rsquared . vimp_se . vrc01 . 
Some associated R codes: average_vim.R . bootstrap_se.R . cv_vim.R . data.R . est_predictiveness.R . est_predictiveness_cv.R . estimate.R . estimate.predictiveness_measure.R . estimate_type_predictiveness.R . extract_sampled_split_predictions.R . format.predictiveness_measure.R . format.vim.R . measure_accuracy.R . measure_anova.R . measure_auc.R . measure_average_value.R . measure_cross_entropy.R . measure_deviance.R . measure_mse.R . measure_r_squared.R . merge_vim.R . predictiveness_measure.R . print.predictiveness_measure.R . print.vim.R . sample_subsets.R . sp_vim.R . spvim_ics.R . spvim_se.R . utils.R . vim.R . vimp-package.R . vimp_accuracy.R . vimp_anova.R . vimp_auc.R . vimp_ci.R . vimp_deviance.R . vimp_hypothesis_test.R . vimp_regression.R . vimp_rsquared.R . vimp_se.R . zzz.R .  Full vimp package functions and examples
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