Suggests: knitr, rmarkdown, testthat, tidyverse, readr, ggpubr, covr,

tidyselect, tidyr, stringr, jmvcore, quantreg, patchwork,
Suggests: knitr, rmarkdown, testthat, tidyverse, readr, covr, mgcv,
Packaged: 2022-08-23 17:03:22 UTC; aaroncaldwell

Description: This package detects instances of Simpson's Paradox in
datasets. It examines subpopulations in the data, either
user-defined or by means of cluster analysis, to test whether a
regression at the level of the group is in the opposite
direction at the level of subpopulations.

Title: Simulation process of 4 selection methods in predicting chemical
Description: This package provides simulation process of 4 selection methods in predicting potent compounds

Depends: stats, graphics, grDevices, utils, R (>= 2.13)

Depends: stats, graphics, grDevices, utils, rcdk, R (>= 2.13)

Title: Correspondence and Simultaneous Analysis
Author: Amaya Zarraga, Beatriz Goitisolo
Description: This package performs classical correspondence analysis
and simultaneous analysis. Simultaneous analysis is a factorial
methodology developed for the joint treatment of a set of
several contingency tables. In this package, functions for
computation, summaries and graphical visualization in two
dimensions are provided, including options to display partial

Description: This package performs classical correspondence analysis (CA) and
simultaneous analysis (SA). Simultaneous analysis is a factorial
methodology developed for the joint treatment of a set of several
contingency tables. In SA tables having the same rows, are concatenated
In this version of the package a multiple option have been included for
of tables having the same columns, concatenated column-wise.
This way, a MSA allows to perform the analysis of an indicator matrix
In this package, functions for computation, summaries
and graphical visualization in two dimensions are provided, including
options to display partial and supplementary points.

generation and survival function for the Sine Inverse Weibull Distribution as
defined by SOUZA, L. New Trigonometric Class of Probabilistic Distributions.