bwd.nrd {etasFLP} | R Documentation |
Silverman's rule optimal for the estimation of a kernel bandwidth
Description
Computes the optimal bandwidth with the Silverman's rule of thumb, to be used for a kernel estimator with given points and weights.
Usage
bwd.nrd(x, w=replicate(length(x),1), d = 2)
Arguments
x |
numeric vector: sample points to be used for a normal kernel estimator. |
w |
numeric vector of the same length of |
d |
number of dimensions of the kernel estimator. |
Details
Computes the optimal bandwidth with the Silverman rule, for a kernel
estimator with points x
and weights w
.
If a multivariate kernel is used, (i.e. d
> 1),
bwd.nrd
must be called for each variable. It computes dispersion only with the weighted standard deviation, with no robust alternative. Called by kde2dnew.fortran
.
Value
The value of the bandwidth for a sample x
and weights w
.
Note
It is used in connection with the the declustering method of etasFLP
. Points with an higher probability of being part of the background seismicity will weight more in the estimation of the background seismicity.
Note
This is a slight modification of bw.nrd
.
Author(s)
Marcello Chiodi
References
Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis. Chapman and Hall: London.
Examples
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