# kde3d: Compute a Three Dimension Kernel Density Estimate In misc3d: Miscellaneous 3D Plots

## Description

Evaluates a three dimensional kernel density estimate using a Gaussian kernel with diagonal covariance matrix on a regular grid.

## Usage

 `1` ``` kde3d(x, y, z, h, n = 20, lims = c(range(x), range(y), range(z))) ```

## Arguments

 `x,y,z` `x`, `y`, and `z` coordinates of the data. `h` vector of three bandwidths for the density estimate; recycled if length is less than three; default is based on the normal reference bandwidth (see `bandwidth.nrd`). `n` numbers of grid points to use for each dimension; recycled if length is less than three. `lims` lower and upper limits on the region for which the density estimate is to be computed, provides as a vector of length 6, corresponding to low and high values of `x`, `y`, and `z`; recycled if only two values are supplied.

## Value

A list of four components, `x`, `y`, `z`, and `d`. `x`, `y`, and `z` are the coordinates of the grid points at which the density estimate has been evaluated, and `d` is a three dimensional array of the estimated density values.

## References

Based on the function `kde2d` in package MASS.

`kde2d`.

## Examples

 ```1 2 3 4 5 6``` ``` with(quakes, { d <- kde3d(long, lat, -depth, n = 40) contour3d(d\$d, exp(-12), d\$x/22, d\$y/28, d\$z/640, color = "green", color2 = "gray", scale=FALSE, engine = "standard") }) ```

### Example output

```
```

misc3d documentation built on May 30, 2017, 2 a.m.