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#' @title The Blaker exact test
#' @description The Blaker exact test for the binomial probability (pi)
#' H_0: pi = pi0 vs H_A: pi ~= pi0 (two-sided)
#' Described in Chapter 2 "The 1x2 Table and the Binomial Distribution"
#
#' @references Blaker H (2000) Confidence curves and improved exact
#' confidence intervals for discrete distributions. The Canadian Journal of
#' Statistics; 28:783-798
#
#' @param X the number of successes
#' @param n the total number of observations
#' @param pi0 a given probability
#' @return An object of the [contingencytables_result] class,
#' basically a subclass of [base::list()]. Use the [utils::str()] function
#' to see the specific elements returned.
#' @examples
#' Blaker_exact_test_1x2(singh_2010["1st", "X"], singh_2010["1st", "n"], pi0 = 0.513)
#' Blaker_exact_test_1x2(singh_2010["2nd", "X"], singh_2010["2nd", "n"], pi0 = 0.513)
#' Blaker_exact_test_1x2(singh_2010["3rd", "X"], singh_2010["3rd", "n"], pi0 = 0.513)
#' Blaker_exact_test_1x2(singh_2010["4th", "X"], singh_2010["4th", "n"], pi0 = 0.513)
#' Blaker_exact_test_1x2(ligarden_2010["X"], ligarden_2010["n"], pi0 = 0.5)
#' @export
Blaker_exact_test_1x2 <- function(X, n, pi0) {
validateArguments(mget(ls()))
# Calculate the two-sided P-value
Pvalues <- dbinom(0:n, n, pi0)
gammaobs <- min(c(sum(Pvalues[(X + 1):(n + 1)]), sum(Pvalues[1:(X + 1)])))
P <- 0
for (k in 0:n) {
gammak <- min(c(sum(Pvalues[(k + 1):(n + 1)]), sum(Pvalues[1:(k + 1)])))
if (gammak <= gammaobs) {
P <- P + dbinom(k, n, pi0)
}
}
# Output
printresults <- function() {
cat_sprintf("The Blaker exact test: P = %7.5f", P)
}
return(contingencytables_result(list("Pvalue" = P), printresults))
}
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