plotAsIntRegGOF: Integrated Regression Goodness of Fit graphical output
In intRegGOF: Integrated Regression Goodness of Fit

Description Usage Arguments Details Note Author(s) See Also Examples

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

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

`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.

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.

lm objects that does not have a data parameter set when the call is executed does not work presently when the covar parameter is different than 0.

Jorge Luis Ojeda Cabrera (jojeda@unizar.es).

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

  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)