plr: Polygonal linear regression

Description Usage Arguments Value References Examples

Description

plr is used to fit polygonal linear models.

Usage

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plr(formula, data, model = TRUE, ...)

Arguments

formula

an object of class "formula": a symbolic description of the model to be fitted.

data

a environment that contains the variables of the study.

model

logicals. If TRUE the corresponding components of the fit are returned.

...

additional arguments to be passed to the low level polygonal linear regression fitting functions.

Value

residuals is calculated as the response variable minus the fitted values.

rank the numeric rank of the fitted polygonal linear model.

call the matched call.

fitted.values the fitted mean values.

terms the terms.

coefficients a named vector of coefficients.

model the matrix model for center and radius.

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, e)

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