Title: Change Point Estimation for Regression with Heteroscedastic Data
Description: Estimation of parameters in 3-segment (i.e. 2 change-point)
regression models with heteroscedastic variances is provided based on both
likelihood and hybrid Bayesian approaches, with and without continuity
Author: Stephen J.Ganocy, Jiayang Sun, and Yulei Wang

Title: Using Historical Controls for Designing Phase II Clinical Trials
Description: Provides functions for designing phase II clinical trials adjusting for the heterogeneity of the population using known subgroups or historical controls.

Title: A Batch Process for High Dimensional Imputation
Authors@R: person("Philip", "Waggoner", role = c("aut", "cre"), email = "philip.waggoner@gmail.com")
Description: A correlation-based batch process for fast imputation for
high dimensional missing data problems via chained random forests.
See Stekhoven and Bühlmann (2012) <doi:10.1093/bioinformatics/btr597>
for more on missForest, and Mayer (2022)
<https://github.com/mayer79/missRanger> for more on missRanger.
Imports: missRanger, plyr, purrr, magrittr, tibble, dplyr, tidyselect,
Packaged: 2022-03-02 15:46:25 UTC; philip.waggoner

Suggests: testthat (>= 3.0.0), knitr, rmarkdown, usethis, missForest,
Packaged: 2022-04-20 20:52:28 UTC; philip.waggoner

Description: Functions to perform dimensionality reduction for
classification if the covariance matrices of the classes are

Description: Functions to perform dimensionality reduction for classification if the covariance matrices of the classes are unequal.

Title: Change-Point Analysis of High-Dimensional Time Series via Binary
person('Haeran', 'Cho', email='haeran.cho@bristol.ac.uk', role=c('aut', 'cre')),
Description: Binary segmentation methods for detecting and estimating
multiple change-points in the mean or second-order structure
of high-dimensional time series as described in Cho and Fryzlewicz (2014) <doi:10.1111/rssb.12079> and Cho (2016) <doi:10.1214/16-EJS1155>.
Imports: Rcpp (>= 0.12.10), foreach, iterators, doParallel