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#' Kinship coefficient and genetic index of familiality
#'
#' @param data the trio data of a pedigree.
#' @param gifset a subgroup of pedigree members.
#'
#' @details
#' The genetic index of familality is defined as the mean kinship between
#' all pairs of individuals in a set multiplied by 100,000. Formally, it
#' is defined in \insertCite{gholami94}{gap} as
#' \deqn{100,000 \times \frac{2}{n(n-1)}\sum_{i=1}^{n-1}\sum_{j=i+1}^n k_{ij}}{100,000 x 2/[n(n-1)]\sum_(i=1)^(n-1)\sum_(j=i+1)^n k_(ij)}
#' where \eqn{n} is the number of individuals in the set and \eqn{k_{ij}} is the
#' kinship coefficient between individuals \eqn{i} and \eqn{j}.
#'
#' The scaling is purely for convenience of presentation.
#'
#' @return
#' The returned value is a list containing:
#' - gifval the genetic index of familiarity.
#'
#' @references
#' \insertAllCited{}
#'
#' @seealso [`pfc`]
#'
#' @examples
#' \dontrun{
#' test<-c(
#' 5, 0, 0,
#' 1, 0, 0,
#' 9, 5, 1,
#' 6, 0, 0,
#' 10, 9, 6,
#' 15, 9, 6,
#' 21, 10, 15,
#' 3, 0, 0,
#' 18, 3, 15,
#' 23, 21, 18,
#' 2, 0, 0,
#' 4, 0, 0,
#' 7, 0, 0,
#' 8, 4, 7,
#' 11, 5, 8,
#' 12, 9, 6,
#' 13, 9, 6,
#' 14, 5, 8,
#' 16, 14, 6,
#' 17, 10, 2,
#' 19, 9, 11,
#' 20, 10, 13,
#' 22, 21, 20)
#' test<-matrix(test,ncol=3,byrow=TRUE)
#' gif(test,gifset=c(20,21,22))
#'
#' # all individuals
#' gif(test,gifset=1:23)
#' }
#'
#' @author Alun Thomas, Jing Hua Zhao
#' @note Adapted from gif.c, testable with -Dexecutable as standalone program,
#' which can be use for any pair of indidivuals
#' @export
#' @keywords datagen
gif <- function(data,gifset)
{
famsize<-dim(data)[1]
giflen<-length(gifset)
gifval<-0
z<-.C("gif_c",data=as.integer(t(data)),famsize=as.integer(famsize),
gifset=as.integer(array(gifset)),giflen=as.integer(giflen),
gifval=as.double(gifval),PACKAGE="gap")
list(gifval=z$gifval)
}
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