# R/kantorovich_lpsolve.R In stla/kantorovich: Kantorovich Distance Between Probability Measures

#### Documented in kantorovich_lp

```#' Computes Kantorovich distance with lp_solve
#'
#' Kantorovich distance using the \code{lpSolve} package
#'
#' @param mu (row margins) probability measure in numeric mode
#' @param nu (column margins) probability measure in numeric mode
#' @param dist matrix, the distance to be minimized on average; if \code{NULL}, the 0-1 distance is used.
#' @param lp.object logical, if \code{FALSE}, the output is the Kantorovich distance; if \code{TRUE}, the output is a \code{\link[lpSolve]{lp.object}}
#' @param solution logical, to use only if \code{lp.object=FALSE}; if \code{TRUE} the solution is returned in the \code{"solution"} attributes of the output
#' @param ... arguments passed to \code{\link[lpSolve]{lp}}
#'
#' @examples
#' mu <- c(1/7,2/7,4/7)
#' nu <- c(1/4,1/4,1/2)
#' kantorovich_lp(mu, nu)
#'
#' @import lpSolve
#' @export
#'
kantorovich_lp <- function(mu, nu, dist=NULL, solution=FALSE, lp.object=FALSE, ...){
m <- length(mu)
n <- length(nu)
# checks
if(m != n) stop("mu and nu do not have the same length")
if(!is.null(dist)){
if(class(dist) != "matrix" || mode(dist) != "numeric") stop("dist must be a numeric matrix")
if(nrow(dist)!=m || ncol(dist)!=m) stop("invalid dimensions of the dist matrix")
}
if(sum(mu)!=1 || sum(nu)!=1 || any(mu<0) || any(nu<0)){
message("Warning: mu and/or nu are not probability measures")
}
#
if(is.null(dist)) dist <- 1-diag(m)
kanto <- lpSolve::lp(direction = "min", objective.in = c(t(dist)),
const.mat = rbind(-diag(m*n), rbind(t(model.matrix(~0+gl(m,n)))[,], t(model.matrix(~0+factor(rep(1:n,m))))[,])),
const.dir = c(rep("<=", m*n), rep("==", m+n)), const.rhs = c(rep(0,m*n), c(mu, nu)), ...)
# status
if(lp.object==FALSE){
if(kanto\$status != 0){
if(kanto\$status == 2){
cat("Error: no feasible solution found")
}else{
cat("Error: status", kanto\$status, "\n")
}
}
}
# output
out <- if(lp.object) kanto else kanto\$objval
if(!lp.object && solution) attr(out, "solution") <- matrix(kanto\$solution, nrow=m, byrow=TRUE)
return(out)
}
```
stla/kantorovich documentation built on May 26, 2017, 9 p.m.