R/MimputeS.R

In MissMech: Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random

#' @rdname Impute
#' @aliases Impute Mimpute MinputeS
#' @usage NULL
#' @export
MimputeS <- function(data, patused, y1, s1, e)
{
  # This function imputes the missing data by Srivastava method,
  # given the observed and ybar and s from complete data set
  # for a single pattern it goeas through each patterns and uses the
  # linear regresion to predict missing given obsrved data and add the
  # residual to impute missing data 
  x <- data
  ni <- nrow(x)
  pp <- ncol(x)
  indm <- which(is.na(patused))
  indo <- which(!is.na(patused))
  pm <- length(indm)
  po <- length(indo)
  a <- matrix(s1[indm, indo], pm, po) %*% solve(s1[indo, indo])
  dif <-  x[, indo] - matrix(y1[indo], ni, po, byrow = TRUE)
  z <- matrix(y1[indm], ni, pm, byrow = TRUE) + dif %*% t(a)
  etta <- matrix(e[, indm], ni, pm) - matrix(e[, indo], ni, po) %*% t(a)
  zij <- z + etta
  x[, indm] <- zij 
  x
}