R/gramschmidt.R

In DongyueXie/bCART: Explore variants of Bayesian trees.

#' @title QR Decomposition via gram schmidt method
#' @description This is an R function from \url{https://rpubs.com/aaronsc32/qr-decomposition-gram-schmidt}
#' @export

gramschmidt <- function(x) {
  x <- as.matrix(x)
  # Get the number of rows and columns of the matrix
  n <- ncol(x)
  m <- nrow(x)

  # Initialize the Q and R matrices
  q <- matrix(0, m, n)
  r <- matrix(0, n, n)

  for (j in 1:n) {
    v = x[,j] # Step 1 of the Gram-Schmidt process v1 = a1
    # Skip the first column
    if (j > 1) {
      for (i in 1:(j-1)) {
        r[i,j] <- t(q[,i]) %*% x[,j] # Find the inner product (noted to be q^T a earlier)
        # Subtract the projection from v which causes v to become perpendicular to all columns of Q
        v <- v - r[i,j] * q[,i]
      }
    }
    # Find the L2 norm of the jth diagonal of R
    r[j,j] <- sqrt(sum(v^2))
    # The orthogonalized result is found and stored in the ith column of Q.
    q[,j] <- v / r[j,j]
  }

  # Collect the Q and R matrices into a list and return
  qrcomp <- list('Q'=q, 'R'=r)
  return(qrcomp)
}