R/lm_loglik.R

In paulnorthrop/oola: Objected-oriented Loglikelihood Adjustment

#' @export
sigma.lmoola <- function (object, use.fallback = TRUE, mle = TRUE, ...) {
  temp <- object
  class(temp) <- "lm"
  NN <- nobs(temp, use.fallback = use.fallback)
  if (mle) {
    PP <- 0
  } else {
    PP <- sum(!is.na(coef(temp)))
  }
  return(sqrt(deviance(temp, ...) / (NN - PP)))
}

#' @export
vcov.lmoola <- function(object, mle = TRUE, ...) {
  temp <- object
  class(temp) <- "lm"
  if (mle) {
    sigmahat <- sigma(object)
    NN <- nobs(temp, use.fallback = TRUE)
    PP <- sum(!is.na(coef(temp)))
    var_sigmahat <- 2 * (NN - PP) * sigma ^ 2 / NN
  } else {
    sigmahat <- sigma(temp)
    vcov_mat <- vcov(temp)
    var_sigmahat <- 2 * sigma ^ 2
  }
}

# I need logLikVec.lm()

# Use coef.lmoola() and vcov.lmoola()
# This distinguishes between the full MLE (sigma also) and sigma estimated
# via the usual moment estimator.