Package: npmlda 1.2.0

npmlda: Non-Parametric Models for Longitudinal Data Analysis

Support the book: Wu CO and Tian X (2018). Nonparametric Models for Longitudinal Data: With Implementation in R. (Chapman & Hall/CRC Monographs on Statistics & Applied Probability); Present global and local smoothing methods for the conditional-mean and conditional-distribution based nonparametric models with longitudinal Data.

Authors:Xin Tian, Colin Wu

npmlda_1.2.0.tar.gz
npmlda_1.2.0.zip(r-4.7-any)npmlda_1.2.0.zip(r-4.6-any)npmlda_1.2.0.zip(r-4.5-any)
npmlda_1.2.0.tgz(r-4.6-any)npmlda_1.2.0.tgz(r-4.5-any)
npmlda_1.2.0.tar.gz(r-4.7-any)npmlda_1.2.0.tar.gz(r-4.6-any)
npmlda_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
npmlda/json (API)

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

Bug tracker:https://github.com/npmldabook/npmlda/issues

Datasets:

On CRAN:

Conda:

3.11 score 26 scripts 135 downloads 21 exports 0 dependencies

Last updated from:445f2085b5. Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64WARNING105
source / vignettesOK143
linux-release-x86_64WARNING135
macos-release-arm64WARNING189
macos-oldrel-arm64WARNING203
windows-develWARNING64
windows-releaseWARNING62
windows-oldrelWARNING59
wasm-releaseOK87

Exports:CVlmCVsplineDXikernel.fitKernel2DKernel3DKernel3D.S2Kh.BwKh.EpKh.NmKh2DKh3DLocalLmLocalLm.BetaLocalLm.Beta.t0LocalLm.X0Newton1varNewton2varNW.WtKernelspline.fitXi

Dependencies: