c(
person(given = "Mathew", family = "Chamberlain", email = "chamberlainphd@gmail.com", role = c( "aut","cre")),
person(given = "Virginia", family = "Savova", email = "virginia.savova@sanofi.com", role = c( "aut")),
person(given = "Richa", family = "Hanamsagar", email = "richa.hanamsagar@sanofi.com", role = c( "aut")),
person(given = "Frank", family = "Nestle", email = "frank.nestle@sanofi.com", role = c( "aut")),
person(given = "Emanuele", family = "de Rinaldis", email = "Emanuele.deRinaldis@sanofi.com", role = c( "aut")),
person("Sanofi US", role = "fnd"))

Significant Variable Selection in Linear Regression
Provide a significant variable selection procedure with different directions (forward, backward, stepwise) based on diverse criteria (Mallows' Cp, AIC, BIC, adjusted r-square, p-value). The algorithm selects a final model with only significant variables based on a correction choice of False Discovery Rate, Bonferroni, or no correction.

Consistent Significance Controlled Variable Selection in Linear
Regression
Provide consistent significance controlled variable selection procedure with different directions (forward, backward, stepwise) based on diverse criteria (Mallows' Cp, AIC, BIC, adjusted r-square, p-value). The algorithm selects a final model with only significant variables based on a correction choice of False Discovery Rate, Bonferroni, or no correction.

Provide consistent significance controlled variable selection procedure with different directions (forward, backward, stepwise) based on diverse criteria (AIC, BIC, adjusted r-square, and p-value). The algorithm selects a final model with only significant variables based on a correction choice of False Discovery Rate, Bonferroni, or no correction.

Provides significance controlled variable selection algorithms with different directions (forward, backward, stepwise) based on diverse criteria (AIC, BIC, adjusted r-square, PRESS, or p-value). The algorithm selects a final model with only significant variables based on a correction choice of False Discovery Rate, Bonferroni, or no correction.