# contourPlot: Overlaid Scatter and Contour Plots In EdSurvey: Analysis of NCES Education Survey and Assessment Data

## Description

Diagnostic plots for regressions can become too dense to interpret. This function helps by adding a contour plot over the points to allow the density of points to be seen, even when an area is entirely covered in points.

## Usage

 ```1 2``` ```contourPlot(x, y, m = 30L, xrange, yrange, xkernel, ykernel, nlevels = 9L, ...) ```

## Arguments

 `x` numeric vector of the `x` data to be plotted `y` numeric vector of the `y` data to be plotted `m` integer value of the number of `x` and `y` grid points `xrange` numeric vector of length two indicating `x`-range of plot; defaults to range(x) `yrange` numeric vector of length two indicating `y`-range of plot. defaults to range(y) `xkernel` numeric indicating the standard deviation of Normal `x` kernel to use in generating contour plot `ykernel` numeric indicating the standard deviation of Normal `y` kernel to use in generating contour plot `nlevels` integer with the number of levels of the contour plot `...` additional arguments to be passed to a plot call that generates the scatter plot and the contour plot

## Author(s)

Yuqi Liao and Paul Bailey

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```## Not run: sdf <- readNAEP(system.file("extdata/data", "M36NT2PM.dat", package = "NAEPprimer")) lm1 <- lm.sdf(composite ~ pared * dsex + sdracem, sdf) # plot the results contourPlot(x=lm1\$fitted.values, y=lm1\$residuals[,1], # use only the first plausible value m=30, xlab="fitted values", ylab="residuals", main="Figure 1") # add a line indicating where the residual is zero abline(0,0) ## End(Not run) ```

### Example output ```Loading required package: car
lfactors v1.0.4

EdSurvey v2.3.2

Attaching package: 'EdSurvey'

The following objects are masked from 'package:base':

cbind, rbind
```

EdSurvey documentation built on May 2, 2019, 7:30 a.m.