intRegGOF (version 0.85-5)

plot: Integrated Regression Goodness of Fit graphical output

Description

Methods to develop model validation and visualization of Integrated Regression Goodness of Fit technique.

Usage

plotAsIntRegGOF(obj, covar = 1, ADD = FALSE, ...)
  pointsAsIntRegGOF(obj,covar=1,...)
  linesAsIntRegGOF(obj,covar=1,...)

Arguments

obj

An object of class lm, glm or nls.

covar

Variable name, number or vector for which Int. Reg. is computed. If it is a number, it reference a covariate in the model frame, while if it is a name refer to data in data frame using in the fitting process.

ADD

If TRUE the plot is added to existing plot.

…

Further parameters to for plotobj command.

Details

Currently, the implementation computes the accumulated residual process against a single covariate (covar). When the value of covar is set to 0, the response is used as the variable whose residual are accumulated against.

Notice that if covar is a vector its lenght should be equal to the number of residuals.

See Also

lm, glm, nls its associated plot method and intRegGOF.

Examples

# NOT RUN {
  n <- 50
  d <- data.frame( X1=runif(n),X2=runif(n))
  d$Y <- 1 + 2*d$X1 + rnorm(n,sd=.125)
  par(ask=TRUE)
  plot( d ) 
  plotAsIntRegGOF(lm(Y~X1+X2,d),covar="X1") 
  plotAsIntRegGOF(a <- lm(Y~X1-1,d)) 
  plotAsIntRegGOF(a,c("X1")) 
  plotAsIntRegGOF(a,0) 
  plotAsIntRegGOF(a,fitted(a)) 
  par(ask=FALSE)
# }