Nonparametric Statistical Methods
Aligned Rank Test
Center Matrix
Confidence interval for a correlation based on a bootstrap.
Two-sample Fligner-Kileen test for homogeneous scales.
k-Sample version of the Fligner-Kileen test for homogeneous scales.
Placement Test for the Behrens-Fisher problem.
Gehan generalization the Wilcoxon two-sample test
Design Function for Robust Analysis of Covariance
Design Function for Robust Analysis of Covariance
Hodges-Lehmann type estimation and confidence intervals.
Hogg's Adaptive Test
Hogg's Q1 and Q2.
Internal Functions
Jonckheere's Test for Ordered Alternatives
Robust Analysis of Covariance under Heterogeneous Slopes for a k-way l...
routine used in the ANCOVA table obtained by kancova
Train a k nearest neighbors (knn) classifer via cross validation (cv).
Mood Median Confidence Interval
Robust Analysis of Covariance under Heterogeneous Slopes
Robust Analysis of Covariance under Heterogeneous Slopes
Robust Analysis of Covariance under Heterogeneous Slopes
Placements.
plot function for knn_cv
Degree of Polynomial Determination
Internal print functions
General scores rank test for two sample problem
random contaminated normal deviates
Fat-Finger Error Contaminated Normal Deviates
Random Laplace.
p-value for a one sample sign test
vanElteren test for stratified analysis
Wilson (score) confidence interval for a population proportion.
Accompanies the book "Nonparametric Statistical Methods Using R, 2nd Edition" by Kloke and McKean (2024, ISBN:9780367651350). Includes methods, datasets, and random number generation useful for the study of robust and/or nonparametric statistics. Emphasizes classical nonparametric methods for a variety of designs --- especially one-sample and two-sample problems. Includes methods for general scores, including estimation and testing for the two-sample location problem as well as Hogg's adaptive method.