Package: cmahalanobis 0.4.0

cmahalanobis: Calculate Distance Measures for a Given List of Data Frames with Factors

It provides functions that calculate Mahalanobis distance, Euclidean distance, Manhattan distance and Chebyshev distance between each pair of species in a list of data frames. These metrics are fundamental in various fields, such as cluster analysis, classification, and other applications of machine learning and data mining, where assessing similarity or dissimilarity between data is crucial. The package is designed to be flexible and easily integrated into data analysis workflows, providing reliable tools for evaluating distances in multidimensional contexts.

Authors:Flavio Gioia [aut, cre]

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cmahalanobis/json (API)

# Install 'cmahalanobis' in R:

install.packages('cmahalanobis', repos = c('https://hflavio12.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.

12 exports 0.49 score 73 dependencies 211 downloads

Last updated 1 days agofrom:31bfbebeea. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Sep 17 2024
R-4.5-win	OK	Sep 17 2024
R-4.5-linux	OK	Sep 17 2024
R-4.4-win	OK	Sep 17 2024
R-4.4-mac	OK	Sep 17 2024
R-4.3-win	OK	Sep 17 2024
R-4.3-mac	OK	Sep 17 2024

Exports:cchebyshev ceuclide cmahalanobis cmanhattan generate_report_cchebyshev generate_report_ceuclide generate_report_cmahalanobis generate_report_cmanhattan pvaluesccheb pvaluesceucl pvaluescmaha pvaluescmanh

Dependencies:backports bit bit64 boot broom cli clipr codetools colorspace cpp11 crayon dplyr fansi farver forcats foreach generics ggplot2 glmnet glue gtable haven hms isoband iterators jomo labeling lattice lifecycle lme4 magrittr MASS Matrix mgcv mice minqa mitml munsell nlme nloptr nnet numDeriv ordinal pan pillar pkgconfig plyr prettyunits progress purrr R6 RColorBrewer Rcpp RcppEigen readr reshape2 rlang rpart scales shape stringi stringr survival tibble tidyr tidyselect tzdb ucminf utf8 vctrs viridisLite vroom withr

Help page	Topics
Calculate the p_values matrix for each species, using Chebyshev distance as a base.	cchebyshev
Calculate the Euclidean distance of a factor in a dataframe.	ceuclide
Calculate the Mahalanobis distance for each species.	cmahalanobis
Calculate a Manhattan distance of a factor in a dataframe.	cmanhattan
Generate a Microsoft Word document about the Chebyshev distance matrix and the p-values matrix with corresponding plots.	generate_report_cchebyshev
Generate a Microsoft Word document about the Euclidean distance matrix and the p-values matrix with relative plots.	generate_report_ceuclide
Generate a Microsoft Word document about Mahalanobis distance matrix and p-values matrix with corresponding plots.	generate_report_cmahalanobis
Generate a Microsoft Word document about the Manhattan distance and the p-values matrices with corresponding plots.	generate_report_cmanhattan
Calculate the p_values matrix for each species, using Chebyshev distance as a base.	pvaluesccheb
Calculate the p_values matrix for each species, using the Euclidean distance as a base.	pvaluesceucl
Calculate p_values matrix for each species, using Mahalanobis distance as a base.	pvaluescmaha
Calculate the p_values matrix for each species, using Manhattan distance as a base.	pvaluescmanh

Package: cmahalanobis 0.4.0

cmahalanobis: Calculate Distance Measures for a Given List of Data Frames with Factors

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