Suggests: BGLR, e1071, ggplot2, knitr, randomForest, rmarkdown

Description: Workbench for testing genomic regression accuracy on

Title: Goodness-of-Fit Tests in High-Dimensional GLMs
Author: Jana Jankova [aut, cre], Rajen Shah [aut], Peter Buehlmann [aut], Richard Samworth [aut]
Description: Methodology for testing nonlinearity in the conditional mean function
in low- or high-dimensional generalized linear models, and the significance of
(potentially large) groups of predictors. Details on the algorithms can be
found in the paper by Jankova, Shah, Buehlmann and Samworth (2019)
Imports: glmnet, randomForest, MASS, stats, RPtests
Packaged: 2019-10-10 14:50:53 UTC; janajankova

Imports: glmnet, randomForest, MASS, stats, RPtests, ranger
Packaged: 2021-01-07 21:03:31 UTC; janajankova

Packaged: 2021-03-17 19:50:43 UTC; janajankova

Title: Gauge R and R Confidence Intervals
Author: Walter Resch with information from 'Measurement System Assessment Via Generalized Inference'
Description: Generates confidence intervals for the variance components in Gauge R and R data using ANOVA
with the Satterthwaite approximation as well as the method of Generalized Inference.

Author: Walter Resch with information from 'Measurement System
Assessment Via Generalized Inference' by Michael Hamada and Sam
Description: Generates confidence intervals for the variance components
for Gauge R and R data using ANOVA with the Satterthwaite
approximation as well as the method of Generalized Inference.

Title: GRS Test for Portfolio Efficiency and Its Statistical Power
Description: Computational resources for test proposed by Gibbons, Ross, Shanken (1989)<DOI:10.2307/1913625>.

Title: GRS Test for Portfolio Efficiency, Its Statistical Power
Analysis, and Optimal Significance Level Calculation
Author: Jae H. Kim <J.Kim@latrobe.edu.au>
It also has the functions for the power analysis and the choice of the optimal level of significance.
The optimal level is determined by minimizing the expected loss from hypothesis testing.

Author: Jae H. Kim <jaekim8080@gmail.com>