silvbw: Silverman's rule of thumb for bandwidth selection
In RostyslavMaiboroda/mixvconc:

Description Usage Arguments Details Value See Also Examples

silvbw calculates quasi-optimal bandwidth for kernel density estimate by weighted sample based on the mixture with varying concentrations approach

1	silvbw(xs, m, delta = 1.7188)

`xs`	a `wtsamp` object representing a sample with distributions of different components.
`m`	a number of component for which the density is estimated.
`delta`	the canonical bandwidth of the kernel used in the estimate.

The default value of delta=1.7188 corresponds to the Epanechnikov kernel.

a numeric value of the Silverman's optimal bandwidth.

Maiboroda R., Sugakova O. "Statistics of mixtures with varying concentrations with application to DNA microarray data analysis". Nonparametric statistics (2012) v.24:1, p. 201 - 215.

#' @examples
set.seed(3)
p <- genunifp(1000,2) # create mixing probabilities
a <- lsweight(p) # calculate minimax weights
# create a weighted sample:
xs <- wtsamp(genormixt(p,c(0,1),c(1,1)),indiv=a)
f<-densgen(xs,1) # create the estimator
h<-silvbw(xs,1) # calculates the bandwidth by the Silverman's rule
curve(f(x,h),-3,3) # plot the graph (estimates N(0,1) density)