scatter3dPETER function

3D plot of a Regression Model

This function makes a 3D plot of the data and the regression function. The user has the choice between different methods to calculate the coefficients for the regression model.

scatter3dPETER(x, y, z, xlab = deparse(substitute(x)),
ylab = deparse(substitute(y)), zlab = deparse(substitute(z)),
revolutions = 0, bg.col = c("white", "black"),
axis.col = if (bg.col == "white") "black" else "white",
surface.col = c("blue", "green", "orange", "magenta", "cyan", "red",
"yellow", "gray"), neg.res.col = "red",
pos.res.col = "green", point.col = "yellow", text.col = axis.col,
grid.col = if (bg.col == "white") "black" else "gray",
fogtype = c("exp2", "linear", "exp", "none"),
residuals = (length(fit) == 1), surface = TRUE, grid = TRUE,
grid.lines = 26, df.smooth = NULL, df.additive = NULL, sphere.size = 1,
threshold = 0.01, speed = 1, fov = 60, fit = "linear", groups = NULL,
parallel = TRUE, model.summary = FALSE)

Arguments

• x, y, z: the coordinates for the points
• xlab, ylab, zlab: the labels for the axis
• revolutions: if the plot should be viewed from different angles
• bg.col, axis.col, surface.col, point.col, text.col, grid.col: define the colour for the background, axis,...
• pos.res.col, neg.res.col: colour for positive and negativ residuals
• fogtype: describes the fogtype, see rgl.bg
• residuals: if the residuals should be plotted
• surface: if the regression function should be plotted or just the points
• grid: if TRUE, the grid is plotted
• grid.lines: number of lines in the grid
• df.smooth: if fit=smooth, the number of degrees of freedom
• df.additive: if fit=additive, the number of degrees of freedom
• sphere.size: a value for calibrating the size of the sphere
• threshold: the minimum size of the sphere, if the size is smaller than the threshold a point is plotted
• speed: if revolutions>0, how fast you make a 360 degree turn
• fov: field-of-view angle, see rgl.viewpoint
• fit: which method should be used for the model; "linear", "quadratic", "smooth" or "additive"
• groups: define groups for the points
• parallel: if groups is not NULL, a parallel shift in the model is made
• model.summary: if the summary should be returned

Returns

No return value, creates a plot.

Details

The user can choose between a linear, quadratic, smoothed or additve model to calculate the coefficients.

References

C. Reimann, P. Filzmoser, R.G. Garrett, and R. Dutter: Statistical Data Analysis Explained. Applied Environmental Statistics with R. John Wiley and Sons, Chichester, 2008.

Author(s)

Peter Filzmoser <P.Filzmoser@tuwien.ac.at > http://cstat.tuwien.ac.at/filz/

Examples

#required library
#require(IPSUR)
data(chorizon)
lit=1
# This example needs additional libraries:
#scatter3dPETER(x=log10(chorizon[chorizon$LITO==lit,"Cr"]), 
#               z=log10(chorizon[chorizon$LITO==lit,"Cr_INAA"]),
#               y=log10(chorizon[chorizon$LITO==lit,"Co"]),
#               xlab="",ylab="",zlab="",
#               neg.res.col=gray(0.6), pos.res.col=gray(0.1), point.col=1, fov=30,
#               surface.col="black",grid.col="gray",sphere.size=0.8)