rockchalk (version 1.1)

mcGraph1: Illustrate the effect of multicollinearity in regression.

Description

This is a set of functions that faciliates the examination of multicollinearity. Suppose the "true" relationship is y[i] = 0.2 * x1[i] + 0.2 * x2[i] + e where e is Normal(0, stde^2).

Usage

mcGraph1(x1, x2, y, ...)

Arguments

x1

a predictor vector

x2

a predictor vector

y

the dependent variable

...

additional parameters passed to persp

Examples

set.seed(12345)
## Create data with x1 and x2 correlated at 0.10
dat <- genCorrelatedData(rho=.1, stde=7)

mcGraph1(dat$x1, dat$x2, dat$y, theta=20, phi=8, ticktype="detailed", nticks=10)