sm.sphere: Nonparametric density estimation for spherical data.
Description
This function creates a density estimate from data which can be viewed
as lying on the surface of a sphere. Directional data form a principal
example. The data are displayed in spherical form and a density estimate
may be superimposed. The angle of view may be altered. An interactive
panel is available to control some features of the estimate and the display.
Only modest amounts of data may be used. The limit will depend on the
memory available.
a list containing the value of the smoothing parameter and the rotation
angles of the displayed plot.
Arguments
lat
a vector giving the latitude component of the data in degrees from the
equator.
long
a vector giving the longitude component of the data in degrees east.
kappa
the smoothing parameter used to construct the density estimate. The kernel
function is a Fisher distribution and kappa is its scale parameter.
Larger values of kappa will produce smaller amounts of smoothing.
hidden
a logical value which, when set to TRUE, will display the points which lie
on the rear side of the displayed sphere. This argument will be ignored
if sphim is set to TRUE.
sphim
a logical value which controls whether a density estimate is constructed
and displayed on the sphere in image form.
addpoints
a logical value which controls whether the data points are added to the
plot of the density estimate.
...
arguments for sm.options.
Side Effects
none.
Details
see Section 1.5 of the reference below.
References
Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for
Data Analysis: the Kernel Approach with S-Plus Illustrations.
Oxford University Press, Oxford.