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)))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.
x coordinate of data
y coordinate of data
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.
Number of grid points in each direction. Can be scalar or a length-2 integer vector.
The limits of the rectangle covered by the grid as c(xl, xu, yl, yu).
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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