plot3d.gqc {grt}

plot3d Method for Class 'gqc'

Description

plot the fitted 3D data set and quadratic decision boundaries.

Usage

## S3 method for class 'gqc'
plot3d(x, fitdb = TRUE, initdb = FALSE,
    lims = NULL, npoints = 100, alpha = .5,
    fill = TRUE, smooth = FALSE, ...)

Arguments

x

object of class gqc

fitdb

logical. If TRUE, the fitted decision bound will be plotted. Default to TRUE

initdb

logical. If TRUE, the decision bound specified by the initial parameters will be plotted. Default to FALSE

lims

column matrix of the x, y, and z limits of the plot. If NULL, limits are calculated from the model matrix of x. Default to NULL.

npoints

number of points per dimension (i.e., x, y, and z) used to plot the decision bound surface. Default is 100.

alpha

alpha value for the decision bound surface(s) ranging from 0 (fully transparent) to 1 (opaque). Default is .5

fill

logical. If TRUE, decision bounds (if fitdb or initdb is set to TRUE) should be drawn with filled surfaces. If FALSE, a wire frame should be used. Default to TRUE.

smooth

logical. If TRUE, smooth shading should be used. Default to FALSE.

...

further arguments.

Details

This function produces a 3D scatter plot of data matrix of x and (optionally) quadratic decision boundaries specified within (i.e., x$par and/or x$initpar), using points3d function in the rgl package and contour3d function in the misc3d package respectively.

References

Daniel Adler, Oleg Nenadic and Walter Zucchini (2003) RGL: A R-library for 3D visualization with OpenGL

See Also

plot.gqc, {plot3d.gqc}

Examples

## Not run: 
data(subjdemo_3d)
fit.3dq <- gqc(response ~ x + y + z, data=subjdemo_3d,
    category=subjdemo_3d$category, zlimit=7)
plot3d(fit.3dq)

## End(Not run)