R/combineCorMats.R

In cbdAmgen/bcgp0a: Bayesian Composite Gaussian Processes

#' Combine correlation matrices.
#'
#' \code{combineCorMats} returns a correlation matrix that is a weighted sum of two
#' other correlation matrices.
#'
#' This creates a correlation matrix, \emph{R}, where \deqn{R = wG + (1-w)L}. In
#' the \code{bcgp} setting, \emph{G} is the global correlation matrix, \emph{L}
#' is the local correlation matrix, and \emph{w} is the weight.
#'
#' @param w A scalar between 0 and 1. In the \code{bcgp} setting, the user will have
#' set a lower and upper bound (the default is to be between 0.5 and 1).
#' @param G An \emph{n x n} correlation matrix, often the result of \code{\link{getCorMat}}
#' @param L An \emph{n x n} correlation matrix, often the result of \code{\link{getCorMat}}
#' @return An \emph{n x n} correlation matrix
#' @family correlation and covariance functions
#' @examples
#' n <- 10
#' d <- 2
#' x <- matrix(runif(n * d), nrow = n, ncol = d)
#' rhoG <- runif(d, 0, 1)
#' rhoL <- runif(d, 0, rhoG)
#' G <- getCorMat(x, rhoG)
#' L <- getCorMat(x, rhoL)
#' w <- runif(1, 0.5, 1)
#' combineCorMats(w, G, L)
#' @export

combineCorMats <- function(w, G, L){

  # If I choose not to export this function, then I'll skip the error-checking
  # since the only time this function would be called is if everything is correct.
  # stopifnot((0 <= w && w <= 1),
  #           checkValidCorMat(G),
  #           checkValidCorMat(L))

  R <- w*G + (1 - w)*L
  return(R)
}