Nothing
M.singly.censored <-
function (data, left.censor, t.df = 3)
{
if ((bad.obs <- sum(!(ok <- is.finite(data)))) > 0) {
is.not.finite.warning(data)
data <- data[ok]
warning(paste(bad.obs, "observations with NA/NaN/Inf in 'data' removed."))
}
if (!is.vector(data, mode = "numeric"))
stop("'data' must be a numeric vector")
if (length(data) < 2)
stop("'data' must have 2 or more observations")
if (!(length(left.censor) == 1))
stop("'left.censor' must be a constant")
if (t.df < 1)
stop("'t.df' should be greater than or equal to 1")
data.name <- deparse(substitute(data))
censoring.name <- deparse(substitute(censored))
censoring.side <- "Left"
output <- fix0205(data, left.censor, alpha = t.df/2, beta = 1)
ret.list <- list(distribution = "Normal", sample.size = output$sample[1],
censoring.side = censoring.side, censoring.levels = output$sample[5],
percent.censored = (100 * output$sample[3])/output$sample[1],
parameters = output$consistent.estimates, n.param.est = 2,
method = paste("M-estimator: t.df =", t.df), data.name = data.name,
censoring.name = censoring.name, bad.obs = bad.obs, var.cov.params = output$covariance.estimates)
oldClass(ret.list) <- "estimateCensored"
ret.list
}
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