Package: IPWboxplot 0.1.2

IPWboxplot: Adapted Boxplot to Missing Observations

Boxplots adapted to the happenstance of missing observations where drop-out probabilities can be given by the practitioner or modelled using auxiliary covariates. The paper of "Zhang, Z., Chen, Z., Troendle, J. F. and Zhang, J.(2012) <doi:10.1111/j.1541-0420.2011.01712.x>", proposes estimators of marginal quantiles based on the Inverse Probability Weighting method.

Authors:Ana Maria Bianco [aut], Graciela Boente [aut], Ana Perez-Gonzalez [aut]

IPWboxplot_0.1.2.tar.gz
IPWboxplot_0.1.2.zip(r-4.7)IPWboxplot_0.1.2.zip(r-4.6)IPWboxplot_0.1.2.zip(r-4.5)
IPWboxplot_0.1.2.tgz(r-4.6-any)IPWboxplot_0.1.2.tgz(r-4.5-any)
IPWboxplot_0.1.2.tar.gz(r-4.7-any)IPWboxplot_0.1.2.tar.gz(r-4.6-any)
IPWboxplot_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
IPWboxplot/json (API)

# Install 'IPWboxplot' in R:

install.packages('IPWboxplot', repos = c('https://anaperezgonzalez.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

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

2.00 score 7 scripts 749 downloads 3 exports 2 dependencies

Last updated from:cd92b532d7. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	121
source / vignettes	OK	192
linux-release-x86_64	OK	125
macos-release-arm64	OK	128
macos-oldrel-arm64	OK	167
windows-devel	OK	82
windows-release	OK	89
windows-oldrel	OK	77
wasm-release	OK	106