```
#' Compute location quotients from regions - industries matrices
#'
#' This function computes location quotients from (incidence) regions - industries matrices. The numerator is the share of a given industry in a given region. The denominator is the share of a this industry in a larger economy (overall country for instance). This index is also refered to as the index of Revealed Comparative Advantage (RCA) following Ballasa (1965), or the Hoover-Balassa index.
#' @param mat An incidence matrix with regions in rows and industries in columns
#' @param binary Logical; shall the returned output be a dichotomized version (0/1) of the location quotient? Defaults to FALSE (the full values of the location quotient will be returned), but can be set to TRUE (location quotient values above 1 will be set to 1 & location quotient values below 1 will be set to 0)
#' @keywords specialization concentration
#' @export
#' @examples
#' ## generate a region - industry matrix
#' mat = matrix (
#' c (100, 0, 0, 0, 0,
#' 0, 15, 5, 70, 10,
#' 0, 20, 10, 20, 50,
#' 0, 25, 30, 5, 40,
#' 0, 40, 55, 5, 0), ncol = 5, byrow = T)
#' rownames(mat) <- c ("R1", "R2", "R3", "R4", "R5")
#' colnames(mat) <- c ("I1", "I2", "I3", "I4", "I5")
#'
#' ## run the function
#' location.quotient (mat)
#' location.quotient (mat, binary = TRUE)
#' @author Pierre-Alexandre Balland \email{p.balland@uu.nl}
#' @seealso \code{\link{RCA}}
#' @references Balassa, B. (1965) Trade Liberalization and Revealed Comparative Advantage, \emph{The Manchester School} \strong{33}: 99-123.
location.quotient <- function(mat, binary = FALSE) {
share_tech_city <- mat / rowSums (mat)
share_tech_total <- colSums (mat) / sum (mat)
if (binary) {
LQ <- t(t(share_tech_city)/ share_tech_total)
LQ[is.na(LQ)] <- 0
LQ[LQ < 1] <- 0
LQ[LQ > 1] <- 1
} else {
LQ <- t(t(share_tech_city)/ share_tech_total)
LQ[is.na(LQ)] <- 0
}
return (LQ)
}
```

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