# scatter3dPETER: 3D plot of a Regression Model In StatDA: Statistical Analysis for Environmental Data

## Description

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.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```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

## Details

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

## Author(s)

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

## 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.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```#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) ```

### Example output

```Loading required package: geoR
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Analysis of Geostatistical Data
For an Introduction to geoR go to http://www.leg.ufpr.br/geoR
geoR version 1.7-5.2.1 (built on 2016-05-02) is now loaded
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