R/coef.plsdof.R

In plsdof: Degrees of Freedom and Statistical Inference for Partial Least Squares Regression

#' Regression coefficients
#' 
#' This function returns the regression coefficients of a plsdof-object.
#' 
#' The function returns the regression coefficients (without intercept) for the
#' optimal number of components.
#' 
#' @param object an object of class "plsdof" that is returned by the functions
#' \code{pls.ic} and \code{pls.cv}.
#' @param ... additional parameters
#' @return regression coefficients.
#' @author Nicole Kraemer
#' @seealso \code{\link{vcov.plsdof}}, \code{\link{pls.model}},
#' \code{\link{pls.ic}}, \code{\link{pls.cv}}
#' @references
#' 
#' Kraemer, N., Sugiyama M. (2011). "The Degrees of Freedom of Partial Least
#' Squares Regression". Journal of the American Statistical Association 106
#' (494) \url{https://www.tandfonline.com/doi/abs/10.1198/jasa.2011.tm10107}
#' 
#' Kraemer, N., Braun, M.L. (2007) "Kernelizing PLS, Degrees of Freedom, and
#' Efficient Model Selection", Proceedings of the 24th International Conference
#' on Machine Learning, Omni Press, 441 - 448
#' @keywords models
#' @examples
#' 
#' 
#' n<-50 # number of observations
#' p<-5 # number of variables
#' X<-matrix(rnorm(n*p),ncol=p)
#' y<-rnorm(n)
#' 
#' 
#' pls.object<-pls.ic(X,y,criterion="bic")
#' mycoef<-coef(pls.object)
#' 
#' @export 
coef.plsdof=function(object,...){
    return(object$coefficients)
}