R/f_sum2.R

In jeff-goldsmith/vbvs.concurrent: Variational Bayes Variable Selection for the Functional Linear Concurrent Model

#' Sum computation 2
#' 
#' Internal function used compute a sum in FPCA-based covariance updates
#' 
#' @param y outcome matrix
#' @param subj.id vector of subject ids
#' @param fixef current estimate of fixed effects
#' @param mu.q.c current value of mu.q.c
#' @param kt number of basis functions
#' @param theta spline basis
#' 
#' @author Jeff Goldsmith \email{ajg2202@@cumc.columbia.edu}
#' 
f_sum2 = function(y, subj.id, fixef, mu.q.c, kt, theta){
  I = dim(mu.q.c)[1]
  kp = dim(mu.q.c)[2]
  ret.sum = matrix(0, nrow = kp*kt, ncol = 1)
  subjs = unique(subj.id)
  
  for(i in 1:I){
    index = which(subj.id == subjs[i])
    ret.sum = ret.sum + kronecker((matrix(mu.q.c[i,])), theta[,index]) %*% matrix(y[index] - fixef[index])
  }
  return(ret.sum)
}