rmsea: Root mean squared error of area
In psda: Polygonal Symbolic Data Analysis

Description Usage Arguments Value References Examples

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 (plr).

1	rmsea(observed, fitted)

`observed`	is the response variable of polygonal linear regression model.
`fitted`	are the polygons obtained from polygonal linear regression model as fitted values of the response variable.

rmsea the value of the root mean squared error of area.

Silva, W.J.F, Souza, R.M.C.R, Cysneiros, F.J.A. (2019) https://www.sciencedirect.com/science/article/pii/S0950705118304052.

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)