| magnitude.contour {ssEDA} | R Documentation |
This function calculates mean magnitude contours at a pre-specified depth.
magnitude.contour(events, h=c(0.3, 0.2, 10), depth=10)
events |
defines the events to be plotted. It is an object of class "subset", generally created by subsetcircle, subsetpolygon, subsetrect or subsetsphere.
|
h |
a vector of length three. It specifies the bandwidths for the kernel function (see Details). |
depth |
specifies the longitude-latitude plane where the b-value contours are plotted. |
The mean magnitude contours are produced using local linear regression technique described in Ruppert and Wand (1994) using a standard trivariate normal kernel. The smoothness of the contours is controlled by the bandwidths of the kernel.
NULL
Edwin Choi (ANU), 1997
Ruppert, D. & Wand, M.P. (1994). Multivariate locally weighted least squares regression. Ann. Statist. 22, 1346–1370.
# This example requires the NZ catalogue
require(ssNZ)
# Remember the parameters of the graphics device
par.reset <- par(no.readonly=TRUE)
# Make the Wellington Catalogue
as.catalogue(subsetrect(NZ, minlat=-42.2, maxlat=-40.5,
minlong=173.6, maxlong=176.0, minday=julian(1,1,1978)),
catname="Wellington")
b <- subsetrect(Wellington, maxdepth=100, minmag=3,
minlat=-42.2, maxlat=-40.5, minlong=173.6, maxlong=176.0,
minday=julian(1,1,1980), maxday=julian(1,1,2000))
par(pty="s")
magnitude.contour(b, h=c(0.25, 0.2, 2), depth=10)
map("nz", add=TRUE, col="red")
par(par.reset)