R/rmsea.R

In psda: Polygonal Symbolic Data Analysis

#' Root mean squared error of area
#' 
#' @description Root mean squared error of area is a meansure proposed by Silva et al. (2019). It
#' is used to evaluate the performance of symbolic polygonal linear regression model (\code{plr}).
#' @param  observed is the response variable of polygonal linear regression model.
#' @param  fitted are the polygons obtained from polygonal linear regression model as fitted
#' values of the response variable.
#' @return rmsea the value of the root mean squared error of area.
#' 
#' @references Silva, W.J.F, Souza, R.M.C.R, Cysneiros, F.J.A. (2019) \url{https://www.sciencedirect.com/science/article/pii/S0950705118304052}.
#' @examples 
#' yp <- psim(10, 10) #simulate 10 polygons of 10 sides
#' xp1 <- psim(10, 10) #simulate 10 polygons of 10 sides
#' xp2 <- psim(10, 10) #simulate 10 polygons of 10 sides
#' e <- new.env()
#' e$yp <- yp
#' e$xp1 <- xp1
#' e$xp2 <- xp2
#' fit <- plr(yp~xp1+xp2-1, e)
#' yp_fitted <- fitted(fit, polygon = TRUE, vertices = 10) #Shows the polygon fitted from plr 
#' rmsea(yp, yp_fitted)
#' @export

rmsea <- function(observed, fitted){
  sqrt(mean((sapply(observed, parea) - sapply(fitted, parea))^2))
}