Title: Analyze Multivariate Phenotypes by Combining Univariate Results
Author: Shuo Li <skyli@bu.edu>, Xuan Liu <liuxuan@bu.edu> and Qiong Yang <qyang@bu.edu>
Description: Combining Univariate Association Test Results of Multiple Phenotypes for Detecting Pleiotropy.

Title: Compute Decision Interval and Average Run Length for CUSUM
Author: Douglas M. Hawkins, David H. Olwell, Boxiang Wang
Description: Computation of decision intervals (H) and average run lengths (ARL) for CUSUM charts.

Author: Douglas M. Hawkins, David H. Olwell, and Boxiang Wang

Description: Computation of decision intervals (H) and average run lengths (ARL) for CUSUM charts. Details of the method are seen in Hawkins and Olwell (2012): Cumulative sum charts and charting for quality improvement, Springer Science & Business Media.

Authors@R: c(person(given = "José", family = "Gama", role = c("aut","cre","trl"),email = "jgama@abo.fi"),
person(given = "Maria", family = "Nyberg", role = "aut"),
person(given = "Göran", family = "Högnäs", role = "ths"),
person(given = "Brian", family = "Foutch", role = "ctb"),
person(given = "Mark", family = "Grundland", role = "ctb"),
person(given = "Neil", family = "Dodgson", role = "ctb"))
Description: Methods for color vision deficiencies (CVD), to help understanding and mitigating issues with CVDs and to generate tests for diagnosis and interpretation.

Authors@R: c(person(given = "Jose", family = "Gama", role = c("aut","cre","trl"),email = "rxprtgama@gmail.com"),

Authors@R: c(person("Wenying", "Deng", role = c("aut", "cre"),
person("Jeremiah Zhe", "Liu", role = c("ctb")))
Implementation of Cross-Validated Kernel Ensemble (CVEK),
a flexible modeling framework for robust nonlinear regression and
hypothesis testing based on ensemble learning with kernel-ridge estimators
Wenying et al. (2018) <arXiv:1811.11025>). It allows user to conduct
nonlinear regression with minimal assumption on the function form by
aggregating nonlinear models generated from a diverse collection of kernel
families. It also provides utilities to test for the estimated nonlinear
effect under this ensemble estimator, using either the asymptotic or
the bootstrap version of a generalized score test.
Suggests: testthat, knitr, rmarkdown, ggplot2, ggrepel