compIntRegProc: Utility functions for Integrated Regression Goodness of Fit
In intRegGOF: Integrated Regression Goodness of Fit

Description Usage Arguments Details Note Author(s)

Core functions for the computation of the Integrated Regression Goodness of Fit

compIntRegProc(y, xord, weig = rep(1, length(y)))
compBootSamp(obj, datLT, B = 999, LINMOD = FALSE)
plotIntRegProc(y, x, weig = rep(1, length(y)), ADD = FALSE, ...)
getModelFrame(obj)
getResiduals(obj,type)

`y`	vector, values to add to compute the Integrated Regression.
`xord`	list of list with the index of covariate points that are less than covariate data. This tells how to cumulate according to covariates,
`weig`	vector of weights, specifically used to fit and compute test statistics when data is selection biased.
`obj`	An object of class `lm`, `glm` or `nls`.
`datLT`	structure as `xord` telling how to cumulate according to covariates.
`B`	Bootstrap resampling size.
`LINMOD`	When `TRUE` and if `obj` is an object of class `lm` Linear Model matrix fitting equations are used.
`x`	vector with covarates to plot
`ADD`	If `TRUE` the plot is added to existing plot.
`type`	Type of residual.
`...`	Further parameters to plot.