c(
person("Henrique", "Jose de Paula Alves", email = "jpahenrique@gmail.com", role= c("aut", "cre")),
person("Ben", "Deivide de Oliveira Batista", email = "ben.deivide@gmail.com", role = "ctb"),
person("Daniel", "Furtado Ferreira", email = "danielff@ufla.br", role= "aut"))
Henrique Jose de Paula Alves [aut, cre],
Ben Deivide de Oliveira Batista [ctb],
Daniel Furtado Ferreira [aut]
This is a statistical tool interactive that provides multivariate statistical tests that are more powerful than traditional Hotelling T2 test and LRT (likelihood ratio test) for the vector of normal mean populations with and without contamination and non-normal populations (Henrique J. P. Alves & Daniel F. Ferreira (2019) <DOI: 10.1080/03610918.2019.1693596>).
tcltk, ggplot2, robustbase, tcltk2, tkrplot, gridExtra, stats,
base, utils, MASS, grDevices, DescToolsAddIns

tcltk, ggplot2, robustbase, tcltk2, tkrplot, gridExtra, stats,
utils, MASS, grDevices, DescToolsAddIns

tcltk, ggplot2, robustbase, tcltk2, gridExtra, stats, utils,
MASS, grDevices, DescToolsAddIns

Use a regularization likelihood method to achieve variable selection purpose, can be used with penalty lasso, smoothly clipped absolute deviations (SCAD) and minimax concave penalty (MCP).
Tuning parameter selection techniques include cross validation (CV), Bayesian information criterion (BIC) (low and high), stability of variable selection (sVS), stability of BIC (sBIC), and stability of estimation (sEST).
More details see Zhao, Jiwei, Yang Yang, and Yang Ning (2018) <arXiv:1703.06379> "Penalized pairwise pseudo likelihood for variable selection with nonignorable missing data." Statistica Sinica.

Use a regularization likelihood method to achieve variable selection purpose. Likelihood can be worked with penalty lasso, smoothly clipped absolute deviations (SCAD), and minimax concave penalty (MCP).
Tuning parameter selection techniques include cross validation (CV), Bayesian information criterion (BIC) (low and high), stability of variable selection (sVS), stability of BIC (sBIC), and stability of estimation (sEST).
More details see Jiwei Zhao, Yang Yang, and Yang Ning (2018) <arXiv:1703.06379> "Penalized pairwise pseudo likelihood for variable selection with nonignorable missing data." Statistica Sinica.