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#' BW ratio calculation
#'
#' Compute the BW ratios from data groups
#'
#'
#' @param X The spectral dataset in the matrix format in which each row contains a single sample.
#' @param groupLabel Group label of samples in the dataset.
#'
#' @return Return BW ratio
#'
#' @author Trung Nghia Vu
#'
#' @seealso \code{\link{createNullSampling}}
#'
#' @examples
#' res=makeSimulatedData();
#' X=res$data;
#' groupLabel=res$label;
#' peakList <- detectSpecPeaks(X,
#' nDivRange = c(128),
#' scales = seq(1, 16, 2),
#' baselineThresh = 50000,
#' SNR.Th = -1,
#' verbose=FALSE
#' );
#' resFindRef<- findRef(peakList);
#' refInd <- resFindRef$refInd;
#' maxShift = 50;
#' Y <- dohCluster(X,
#' peakList = peakList,
#' refInd = refInd,
#' maxShift = maxShift,
#' acceptLostPeak = TRUE, verbose=FALSE);
#' # find the BW-statistic
#' BW = BWR(Y, groupLabel);
#'
#' @export
#'
#'
BWR <-function(X, groupLabel)
{
groupNum=length(levels(groupLabel));
m=colMeans(X);
groupMean=list();
groupW=list();
B=X;
B[,]=0;
for (i in 1:groupNum){
groupLabeli=which(groupLabel==levels(groupLabel)[i]);
Xi=X[groupLabeli,]
mi=colMeans(Xi);
groupMean[[i]]=mi;
tempi=matrix(data=rep(mi,nrow(Xi)),nrow=nrow(Xi),
ncol=length(mi),byrow=TRUE);
Wi=(Xi-tempi)^2;
groupW[[i]]=Wi;
temp=matrix(data=rep(m,nrow(Xi)),nrow=nrow(Xi),
ncol=length(m),byrow=TRUE);
B[groupLabeli,]=(tempi-temp)^2;
}
BW=double(ncol(B));
for (i in seq_along(BW)){
BW_denominator=0;
for (j in 1:groupNum){
BW_denominator=BW_denominator+sum(groupW[[j]][,i]);
}
Bw_numerator=sum(B[,i]);
BW[i]=Bw_numerator/BW_denominator;
}
return(BW);
}
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