plot.regvec3d | R Documentation |
The plot method for regvec3d
objects uses the low-level graphics tools in this package to draw 3D and 3D
vector diagrams reflecting the partial and marginal
relations of y
to x1
and x2
in a bivariate multiple linear regression model,
lm(y ~ x1 + x2)
.
The summary
method prints the vectors and their vector lengths, followed by the summary
for the model.
## S3 method for class 'regvec3d' plot( x, y, dimension = 3, col = c("black", "red", "blue", "brown", "lightgray"), col.plane = "gray", cex.lab = 1.2, show.base = 2, show.marginal = FALSE, show.hplane = TRUE, show.angles = TRUE, error.sphere = c("none", "e", "y.hat"), scale.error.sphere = x$scale, level.error.sphere = 0.95, grid = FALSE, add = FALSE, ... ) ## S3 method for class 'regvec3d' summary(object, ...) ## S3 method for class 'regvec3d' print(x, ...)
x |
A “regvec3d” object |
y |
Ignored; only included for compatibility with the S3 generic |
dimension |
Number of dimensions to plot: |
col |
A vector of 5 colors. |
col.plane |
Color of the base plane in a 3D plot or axes in a 2D plot |
cex.lab |
character expansion applied to vector labels. May be a number or numeric vector corresponding to the the
rows of |
show.base |
If |
show.marginal |
If |
show.hplane |
If |
show.angles |
If |
error.sphere |
Plot a sphere (or in 2D, a circle) of radius proportional to the length of
the residual vector, centered either at the origin ( |
scale.error.sphere |
Whether to scale the error sphere if |
level.error.sphere |
The confidence level for the error sphere, applied if |
grid |
If |
add |
If |
... |
Parameters passed down to functions [unused now] |
object |
A |
A 3D diagram shows the vector y
and the plane formed by the predictors,
x1
and x2
, where all variables are represented in deviation form, so that
the intercept need not be included.
A 2D diagram, using the first two columns of the result, can be used to show the projection
of the space in the x1
, x2
plane.
The drawing functions vectors
and link{vectors3d}
used by the plot.regvec3d
method only work
reasonably well if the variables are shown on commensurate scales, i.e., with
either scale=TRUE
or normalize=TRUE
.
None
Fox, J. (2016). Applied Regression Analysis and Generalized Linear Models, 3rd ed., Sage, Chapter 10.
regvec3d
, vectors3d
, vectors
Other vector diagrams:
Proj()
,
arc()
,
arrows3d()
,
circle3d()
,
corner()
,
pointOnLine()
,
regvec3d()
,
vectors3d()
,
vectors()
if (require(carData)) { data("Duncan", package="carData") dunc.reg <- regvec3d(prestige ~ income + education, data=Duncan) plot(dunc.reg) plot(dunc.reg, dimension=2) plot(dunc.reg, error.sphere="e") summary(dunc.reg) # Example showing Simpson's paradox data("States", package="carData") states.vec <- regvec3d(SATM ~ pay + percent, data=States, scale=TRUE) plot(states.vec, show.marginal=TRUE) plot(states.vec, show.marginal=TRUE, dimension=2) summary(states.vec) }
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