kde2d | R Documentation |

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

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

`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 |

`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 |

A list of three components.

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

`z` |
An |

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

```
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")
```

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