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#' @title Cramer - von Mises statistics
#'
#' @description Calculates the Cramer-von Mises test statistic \deqn{T(S_n)=\frac{1}{2q}\sum_{i=1}^{2q}\left(H^-_n(S_{n,i})-H^+_n(S_{n,i})\right)^2} where \eqn{H^-_n(\cdot)} and \eqn{H^+_n(\cdot)} are the empirical CDFs of the the sample of baseline covariates close to the cutoff from the left and right, respectively. See equation (12) in Canay and Kamat (2017).
#' @param Sn Numeric. The pooled sample of induced order statistics. The first column of S can be viewed as an independent sample of W conditional on Z being close to zero from the left. Similarly, the second column of S can be viewed as an independent sample of W conditional on Z being close to the cutoff from the right. See section 3 in Canay and Kamat (2017).
#' @return Returns the numeric value of the Cramer - von Mises test statistic.
#' @author Maurcio Olivares
#' @author Ignacio Sarmiento Barbieri
#' @references
#' Canay, I and Kamat V, (2018) Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design. The Review of Economic Studies, 85(3): 1577-1608
#' @keywords permutation test rdperm
#' @export
CvM.stat <- function(Sn){
q <- length(Sn)/2
Ind_left<-outer(Sn[1:q],Sn,"<=")
H_left<-apply(Ind_left,2,sum)/q
Ind_right<-outer(Sn[(q+1):(2*q)],Sn,"<=")
H_right<-apply(Ind_right,2,sum)/q
return(sum((H_left-H_right)^2)/(2*q))
}
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