# regr2.plot

From HH v3.1-35
0th

Percentile

##### 3D plot of z against x and y, with regression plane fit and display of squared residuals.

3D plot of z against x and y, with regression plane fit and display of squared residuals.

Keywords
models, regression
##### Usage
regr2.plot(x, y, z,
main.in="put a useful title here",
resid.plot=FALSE,
plot.base.plane=TRUE,
plot.back.planes=TRUE,
plot.base.points=FALSE,
eye=NULL,                   ## S-Plus
theta=0, phi=15, r=sqrt(3), ticktype="detailed", ## R
...)
##### Arguments
x,y,z

See

main.in

main title for plot.

resid.plot

Argument to resid.squares.

plot.base.plane, plot.back.planes, plot.base.points

Should these items be plotted?

eye

S-Plus only. See

theta, phi, r, ticktype

R only. See

Other arguments to persp.

##### Value

"Viewing Transformation" for projecting 3D coordinates (x,y,z) into the 2D plane. See persp for details.

##### Note

This plot is designed as a pedagogical example for introductory courses. When resid.plot=="square", then we actually see the set of squares for which the sum of their areas is minimized by the method of "least squares". The demo called in the examples section shows the geometry of regression coefficients, the change in predicted y when x1 is changed one unit holding all other x variables constant.

##### References

Heiberger, Richard M. and Holland, Burt (2004b). Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS. Springer Texts in Statistics. Springer. ISBN 0-387-40270-5.

Smith, W. and Gonick, L. (1993). The Cartoon Guide to Statistics. HarperCollins.

resid.squares, regr1.plot, persp

• regr2.plot
##### Examples
# NOT RUN {
data(fat)
regr2.plot(fat[,"abdomin"], xlab="abdomin",
fat[,"biceps"],  ylab="biceps",
fat[,"bodyfat"], zlab="bodyfat",
resid.plot="square",
eye=c(335.5, 115.65, 171.9),   ## used only in S-Plus
theta=140, phi=35, r=sqrt(15), ## used only in R
box=is.R(),
plot.back.planes=FALSE,
main="Least-squares with two X-variables")

# }
# NOT RUN {