regr2.plot | R Documentation |
3D plot of z against x and y, with regression plane fit and display of squared residuals.
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
...)
x , y , z |
See
|
main.in |
|
resid.plot |
Argument to |
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 |
"Viewing Transformation" for projecting 3D coordinates (x,y,z)
into the 2D plane. See persp
for details.
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.
Richard M. Heiberger <rmh@temple.edu>
Heiberger, Richard M. and Holland, Burt (2015). Statistical Analysis and Data Display: An Intermediate Course with Examples in R. Second Edition. Springer-Verlag, New York. https://link.springer.com/book/10.1007/978-1-4939-2122-5
Smith, W. and Gonick, L. (1993). The Cartoon Guide to Statistics. HarperCollins.
resid.squares
, regr1.plot
, persp
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)
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