rockchalk (version 1.4)

mcGraph3: mcGraph3 draws a 3-dimensional scatter and a regression plane

Description

The observations are scattered in 3-dimensions, the fitted values are represented by a mesh, and their shadows in the x1-x2 plane are also represented.

Usage

mcGraph3(x1, x2, y, interaction = FALSE,
    drawArrows = TRUE, x1lab, x2lab, ylab, ...)

Arguments

x1

a predictor vector

x2

a predictor vector

y

the dependent variable

interaction

a TRUE or FALSE request for inclusion of the x1-x2 interaction in the regression calculation

drawArrows

TRUE or FALSE, do you want arrows from the plane to observed y?

x1lab

label for the x1 axis, (the one called "xlab" inside persp)

x2lab

label for the x2 axis, (the one called "ylab" inside persp)

ylab

label for the y (vertical) axis (the one called "zlab" inside persp)

...

optional arguments passed to persp

Value

• a list of 2 objects, the fitted regression model and the perspective matrix used with persp to draw the image.

Examples

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

mcGraph3(dat$x1, dat$x2, dat$y, theta = 0)

dat2 <- genCorrelatedData(rho = 0, stde = 7)

mcGraph3(dat2$x1, dat2$x2, dat2$y, theta = 0, phi = 10)
mcGraph3(dat2$x1, dat2$x2, dat2$y, theta = 30, phi = 10)
mcGraph3(dat2$x1, dat2$x2, dat2$y, theta = -30, phi = 10)
mcGraph3(dat2$x1, dat2$x2, dat2$y, theta = -30, phi = -10)
mcGraph3(dat2$x1, dat2$x2, dat2$y, theta = -30, phi = -15)

## Run regressions with not-strongly correlated data
modset1 <- list()
for(i in 1:20){
  dat2 <- genCorrelatedData(rho = .1, stde = 7)
  summary(lm( y ~ x1 + x2 , data = dat2))
  modset1[[i]] <- mcGraph3(dat2$x1, dat2$x2, dat2$y, theta = -30)
}


## Run regressions with strongly correlated data
modset2 <- list()
for(i in 1:20){
  dat2 <- genCorrelatedData(rho = .981, stde = 7)
  summary(lm( y ~ x1 + x2 , data = dat2))
  modset2[[i]] <- mcGraph3(dat2$x1, dat2$x2, dat2$y, theta = -30)
}

dat3 <- genCorrelatedData(rho = .981, stde = 100, beta=c(0.1, 0.2, 0.3, -0.1))
mcGraph3(dat3$x1, dat3$x2, dat3$y, theta=-10, interaction = TRUE)