Nothing
'#
Authors
Torsten Pook, torsten.pook@uni-goettingen.de
Copyright (C) 2017 -- 2020 Torsten Pook
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License
as published by the Free Software Foundation; either version 3
of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
'#
#' Miesenberger Index
#'
#' Function to selection index weights according to Miesenberger 1997
#' @param V1 Inverted phenotypic covarianz matrix
#' @param V Phenotypic covarianz matrix
#' @param G Genomic covarianz matrix
#' @param RG Genomic correlation matrix
#' @param r reliability for the breeding value estimation
#' @param w relative weighting of each trait (per genetic SD)
#' @param zw Estimated breeding value
#' @return weights of the selection index
miesenberger.index <- function(V, G, V1=NULL, RG=NULL, r, w, zw=NULL){
if(length(V1)==0){
V1 <- chol2inv(chol(V))
}
if(length(RG)==0){
RG <- sqrt(diag(1/diag(G))) %*% G %*% sqrt(diag(1/diag(G)))
}
d <- nrow(G)
A <- RG * matrix(sqrt(diag(G)), nrow=d, ncol=d, byrow=TRUE) *
matrix(sqrt(diag(V)), nrow=d, ncol=d, byrow=FALSE) *
matrix(r, nrow=d, ncol=d, byrow=FALSE)
bM <- as.numeric(V1 %*% A %*% w)
if(length(zw)==0){
return(bM)
} else{
IM <- sum( bM * zw )
return(IM)
}
}
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