# kde2d: Two-Dimensional Kernel Density Estimation In MASS: Support Functions and Datasets for Venables and Ripley's MASS

## Description

Two-dimensional kernel density estimation with an axis-aligned bivariate normal kernel, evaluated on a square grid.

## Usage

 `1` ```kde2d(x, y, h, n = 25, lims = c(range(x), range(y))) ```

## Arguments

 `x` x coordinate of data `y` y coordinate of data `h` vector of bandwidths for x and y directions. Defaults to normal reference bandwidth (see `bandwidth.nrd`). A scalar value will be taken to apply to both directions. `n` Number of grid points in each direction. Can be scalar or a length-2 integer vector. `lims` The limits of the rectangle covered by the grid as `c(xl, xu, yl, yu)`.

## Value

A list of three components.

 `x, y` The x and y coordinates of the grid points, vectors of length `n`. `z` An `n` by `n` matrix of the estimated density: rows correspond to the value of `x`, columns to the value of `y`.

## References

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24``` ```attach(geyser) plot(duration, waiting, xlim = c(0.5,6), ylim = c(40,100)) f1 <- kde2d(duration, waiting, n = 50, lims = c(0.5, 6, 40, 100)) image(f1, zlim = c(0, 0.05)) f2 <- kde2d(duration, waiting, n = 50, lims = c(0.5, 6, 40, 100), h = c(width.SJ(duration), width.SJ(waiting)) ) image(f2, zlim = c(0, 0.05)) persp(f2, phi = 30, theta = 20, d = 5) plot(duration[-272], duration[-1], xlim = c(0.5, 6), ylim = c(1, 6),xlab = "previous duration", ylab = "duration") f1 <- kde2d(duration[-272], duration[-1], h = rep(1.5, 2), n = 50, lims = c(0.5, 6, 0.5, 6)) contour(f1, xlab = "previous duration", ylab = "duration", levels = c(0.05, 0.1, 0.2, 0.4) ) f1 <- kde2d(duration[-272], duration[-1], h = rep(0.6, 2), n = 50, lims = c(0.5, 6, 0.5, 6)) contour(f1, xlab = "previous duration", ylab = "duration", levels = c(0.05, 0.1, 0.2, 0.4) ) f1 <- kde2d(duration[-272], duration[-1], h = rep(0.4, 2), n = 50, lims = c(0.5, 6, 0.5, 6)) contour(f1, xlab = "previous duration", ylab = "duration", levels = c(0.05, 0.1, 0.2, 0.4) ) detach("geyser") ```

### Example output        ```
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MASS documentation built on May 3, 2021, 5:08 p.m.