rmsea: Root mean squared error of area

Description Usage Arguments Value References Examples

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 (plr).

Usage

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rmsea(observed, fitted)

Arguments

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.

Value

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) https://www.sciencedirect.com/science/article/pii/S0950705118304052.

Examples

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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)

psda documentation built on June 25, 2019, 1:03 a.m.