# regr2.plot: 3D plot of z against x and y, with regression plane fit and... In HH: Statistical Analysis and Data Display: Heiberger and Holland

## Description

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

## Usage

 ```1 2 3 4 5 6 7 8 9``` ```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 `persp`. `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 `persp`. `theta, phi, r, ticktype` R only. See `persp`. `...` 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.

## Author(s)

Richard M. Heiberger <[email protected]>

## 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`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```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: demo("regr2", package="HH", ask=FALSE) ## run the file manually to see the individual steps. ## End(Not run) ```