kde2d {MASS} | 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. |
n |
Number of grid points in each direction. |
lims |
The limits of the rectangle covered by the grid as c(xl, xu, yl, yu) .
|
x, |
The x and y coordinates of the grid points, vectors of length n .
|
z |
An n x n matrix of the evaluated density.
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data(geyser) 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")