ezsim provides a handy way to run simulation and examine
its result

provide an easy to use framework to conduct simulation
foreach, ggplot2, reshape, plyr, parallel, Jmisc, digest

ezsim provides a handy way to run simulation and examine its result
foreach, ggplot2, parallel, digest, plyr, reshape, Jmisc

Summarise Data in the Quick and Easy Way
person("Hao", "Zhu", email = "haozhu@hsl.harvard.edu", role = c("aut", "cre"))
Functions that can fulfill the gap between the outcomes of 'dplyr' and a print-ready summary table.

Generate Data Summarization in a Tidy Format
c(
person("Hao", "Zhu", email = "haozhu233@gmail.com", role = c("aut", "cre")),
person("Thomas", "Travison", email = "TGT@hsl.harvard.edu", role = c("ctb")),
person("Timothy", "Tsai", email = "TimothyTsai@hsl.harvard.edu", role = c("ctb")),
person("Akhmed", "Umyarov", email = "aumyarov@umn.edu", role = c("ctb"))
)
Functions that simplify the process of generating print-ready data summarization using 'dplyr' syntax.
Hao Zhu [aut, cre],
Thomas Travison [ctb],
Timothy Tsai [ctb],
Akhmed Umyarov [ctb]

Functions that simplify the process of generating print-ready data summary using 'dplyr' syntax.

This package contains a collection of R functions to
perform nonparametric analysis of covariance for regression
curves or surfaces. Testing the equality or parallelism of
nonparametric curves or surfaces is equivalent to analysis of
variance (ANOVA) or analysis of covariance (ANCOVA) for
one-sample functional data. Three different testing methods are
available in the package, including one based on L-2 distance,
one based on an ANOVA statistic, and one based on variance
estimators.

c(
person(given = "Xiaofeng",
family = "Wang",
role = c("aut", "cre"),
email = "wangx6@ccf.org"),
person(given = "Xinge",
family = "Ji",
role = c("ctb"),
email = "jix@ccf.org"))
A collection of R functions to perform nonparametric
analysis of covariance for regression curves or surfaces.
Testing the equality or parallelism of nonparametric curves
or surfaces is equivalent to analysis of variance (ANOVA) or
analysis of covariance (ANCOVA) for one-sample functional data.
Three different testing methods are available in the package,
including one based on L-2 distance, one based on an ANOVA
statistic, and one based on variance estimators.
Xiaofeng Wang [aut, cre],
Xinge Ji [ctb]