R/residuals.augSIMEX.R

In augSIMEX: Analysis of Data with Mixed Measurement Error and Misclassification in Covariates

residuals.augSIMEX <- function (object, type = c("deviance", "pearson", "working", 
                           "response", "partial"), ...) 
{ type <- match.arg(type)
  y <- object$y
  r <- object$residuals
  mu <- object$fitted.values
  wts <- object$weights
  switch(type, deviance = , pearson = , response = if (is.null(y)) {
    mu.eta <- object$family$mu.eta
    eta <- object$linear.predictors
    y <- mu + r * mu.eta(eta)
  })
  res <- switch(type, deviance = if (object$df.residual > 0) {
    d.res <- sqrt(pmax((object$family$dev.resids)(y, mu, 
                                                  wts), 0))
    ifelse(y > mu, d.res, -d.res)
  } else rep.int(0, length(mu)), pearson = (y - mu) * sqrt(wts)/sqrt(object$family$variance(mu)), 
  working = r, response = y - mu, partial = r)
  if (!is.null(object$na.action)) 
    res <- naresid(object$na.action, res)
  if (type == "partial") 
    res <- res + predict(object, type = "terms")
  res
}