# kde2d

##### Two-Dimensional Kernel Density Estimation

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

- Keywords
- dplot

##### Usage

`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.

The x and y coordinates of the grid points, vectors of length `n`

.

An `n[1]`

by `n[2]`

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

```
# NOT RUN {
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")
# }
```

*Documentation reproduced from package MASS, version 7.3-51.4, License: GPL-2 | GPL-3*