plot.PLreg: Diagnostic Plots for PLreg Objects

In PLreg: Power Logit Regression for Modeling Bounded Data

Diagnostic Plots for PLreg Objects

Description

This function provides plots for diagnostic analysis of power logit regression models.

Usage

## S3 method for class 'PLreg'
plot(x, which = 1:4, type = "standardized", pch = "+", las = 1, cex = 0.8, ...)

Arguments

x	fitted model object of class "PLreg".
which	numeric specifying a subset of plots (numbers between 1 and 7). Default is which = 1:4.
type	character specifying the type of residuals, see residuals.PLreg. Default is type = "standardized".
pch, las, cex, ...	graphical parameters (see par)

Details

The plot method for PLreg objects provides 7 types of diagnostic plots in the following order.

Residuals vs indexes of obs.

An index plot of the residuals versus indexes of observations.

Case-weight perturbation

An index plot of local influence based on the case-weight perturbation scheme.

Generalized leverage

A dispersion diagram of the generalized leverage versus the predicted values.

Residuals vs linear predictor

A dispersion diagram of the residuals versus the linear predictors.

Normal probability plot

A normal probability plot of the residuals.

Predicted vs observed values

A dispersion diagram of the predicted values versus the observed values.

Residuals vs v(z) function

A dispersion diagram of the v(z) function versus the residuals. For some power logit models, the v(z) function may be interpreted as weights in the estimation process. If family = "NO", the v(z) function is constant.

The which argument can be used to select a subset of the implemented plots. Default is which = 1:4.

Value

plot method for PLreg objects returns 7 types of diagnostic plots.

See Also

PLreg, residuals.PLreg, envelope, influence

Examples

data("Firm")

fitPL <- PLreg(firmcost ~ sizelog + indcost | sizelog + indcost, data = Firm,
              family = "SLASH", zeta = 2.13)
par(mfrow = c(3,3))
plot(fitPL, type = "standardized")
par(mfrow = c(1, 1))

PLreg documentation built on Feb. 16, 2023, 7:26 p.m.