Package: compindPCA 0.1.0

compindPCA: Computation of Relative Weights of Variables and Composite Index Values Based on PCA

It helps in development of a principal component analysis based composite index by assigning weights to variables and combining the weighted variables. For method details see Sendhil, R., Jha, A., Kumar, A. and Singh, S. (2018). <doi:10.1016/j.ecolind.2018.02.053>, and Wu, T. (2021). <doi:10.1016/j.ecolind.2021.108006>.

Authors:Sudipta Paul [aut, ctb], Rajeev Ranjan Kumar [aut, cre], Mrinmoy Ray [ctb], Biswajit Mondal [ctb], Prakash Kumar [ctb]

compindPCA_0.1.0.tar.gz
compindPCA_0.1.0.zip(r-4.5)compindPCA_0.1.0.zip(r-4.4)compindPCA_0.1.0.zip(r-4.3)
compindPCA_0.1.0.tgz(r-4.4-any)compindPCA_0.1.0.tgz(r-4.3-any)
compindPCA_0.1.0.tar.gz(r-4.5-noble)compindPCA_0.1.0.tar.gz(r-4.4-noble)
compindPCA_0.1.0.tgz(r-4.4-emscripten)compindPCA_0.1.0.tgz(r-4.3-emscripten)
compindPCA.pdf |compindPCA.html✨
compindPCA/json (API)

# Install 'compindPCA' in R:

install.packages('compindPCA', repos = c('https://rrk4910.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

Data_sample - Sample data for the PCA based compositive index.

On CRAN:

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

1.00 score 1 scripts 173 downloads 1 exports 111 dependencies

Last updated 2 years agofrom:89cbfa1a64. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 13 2024
R-4.5-win	OK	Nov 13 2024
R-4.5-linux	OK	Nov 13 2024
R-4.4-win	OK	Nov 13 2024
R-4.4-mac	OK	Nov 13 2024
R-4.3-win	OK	Nov 13 2024
R-4.3-mac	OK	Nov 13 2024