Nothing
aout.mvnorm <-
function(data, param, alpha = 0.1, hide.outliers = FALSE){
# check arguments
if (!identical(all.equal(length(param), 2), TRUE))
stop("param must be a list with two elements.")
if (!is.vector(param[[1]]))
stop("First entry of param must be the mean vector.")
if (!is.matrix(param[[2]]))
stop("Second entry of param must be the covariance matrix.")
if (is.data.frame(data)) as.matrix(data)
if (!is.matrix(data))
stop("data must be a data.frame or matrix.")
if (!identical(all.equal(length(alpha), 1), TRUE) | alpha <= 0 | alpha >= 1)
stop("alpha must be a real number between 0 and 1, but it is ", alpha, ".")
# end check arguments
# determine the outlier region
n <- nrow(data)
d <- ncol(data)
te1 <- numeric(n)
for (i in 1:n){
te1[i] <- (t(data[i,] - param[[1]])) %*% solve(param[[2]]) %*% (data[i,] - param[[1]])
}
temp.region <- qchisq(df = d, 1 - alpha)
# give the results of the analysis
temp <- data.frame(data = data, is.outlier = (te1 > temp.region))
if (identical(all.equal(hide.outliers, FALSE), TRUE)) temp
else temp[temp[,d+1] == FALSE, -(d+1)]
}
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