Core Functions {intRegGOF}

Utility functions for Integrated Regression Goodness of Fit

Description

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

Usage

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)

Arguments

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.

Details

...TODO: Each of them computes what in which way

Note

Surely they can better implemented.

Author(s)

Jorge Luis Ojeda Cabrera ([e-mail]).