Nothing
aout.binom <-
function(data, param, alpha = 0.1, hide.outliers = FALSE){
# check arguments
if (!is.numeric(param) | !is.vector(param) | !identical(all.equal(length(param), 2), TRUE))
stop("param must be a numeric vector of length 2.")
if (!identical(all.equal(param[1], round(param[1])), TRUE))
stop("First element of param must be the sample size (an integer).")
if (param[2] <= 0 | param[2] >= 1)
stop("Second element of param must be the probability of success (between 0 and 1).")
if (!is.numeric(data) | !is.vector(data))
stop("data must be a numeric vector.")
if (any(data > param[1]))
stop("No element of data may be larger than ", param[1], ".")
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
size <- param[1]
prob <- param[2]
x <- 0:size
prob.vector <- dbinom(x, size, prob)
temp.region <- order(prob.vector)[which(cumsum(sort(prob.vector)) < alpha)] - 1
# give the results of the analysis
temp <- data.frame(data = data, is.outlier = (data %in% temp.region))
if (hide.outliers == FALSE) temp
else temp[temp[,2] == FALSE, 1]
}
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