Package: nparLD 2.2

nparLD: Nonparametric Analysis of Longitudinal Data in Factorial Experiments

Performs nonparametric analysis of longitudinal data in factorial experiments. Longitudinal data are those which are collected from the same subjects over time, and they frequently arise in biological sciences. Nonparametric methods do not require distributional assumptions, and are applicable to a variety of data types (continuous, discrete, purely ordinal, and dichotomous). Such methods are also robust with respect to outliers and for small sample sizes.

Authors:Kimihiro Noguchi <[email protected]>, Mahbub Latif <[email protected]>, Karthinathan Thangavelu, Frank Konietschke <[email protected]>, Yulia R. Gel <[email protected]>, Edgar Brunner <[email protected]>

nparLD_2.2.tar.gz
nparLD_2.2.zip(r-4.7)nparLD_2.2.zip(r-4.6)nparLD_2.2.zip(r-4.5)
nparLD_2.2.tgz(r-4.6-any)nparLD_2.2.tgz(r-4.5-any)
nparLD_2.2.tar.gz(r-4.7-any)nparLD_2.2.tar.gz(r-4.6-any)
nparLD_2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
nparLD/json (API)

# Install 'nparLD' in R:
install.packages('nparLD', repos = c('https://frankkonietschke.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.30 score 3 stars 67 scripts 801 downloads 90 mentions 10 exports 1 dependencies

Last updated from:d68a38b69a. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK126
source / vignettesOK197
linux-release-x86_64OK114
macos-release-arm64OK136
macos-oldrel-arm64OK150
windows-develOK78
windows-releaseOK72
windows-oldrelOK71
wasm-releaseOK88

Exports:f1.ld.f1f1.ld.f2f2.ld.f1ld.cild.f1ld.f2nparLDplot.nparLDprint.nparLDsummary.nparLD

Dependencies:MASS