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)
vector, values to add to compute the Integrated Regression.
list of list with the index of covariate points that are less than covariate data. This tells how to cumulate according to covariates,
vector of weights, specifically used to fit and compute test statistics when data is selection biased.
structure as xord
telling how to cumulate according
to covariates.
Bootstrap resampling size.
When TRUE
and if obj
is an object of class
lm
Linear Model matrix fitting equations are used.
vector with covarates to plot
If TRUE
the plot is added to existing plot.
Type of residual.
Further parameters to plot.
...TODO: Each of them computes what in which way