R/bw.mse.pdf.asym.R In MRPP: Multiresponse permutation procedure and its variable importance and variable selection methods.

```bw.mse.pdf.asym=function(x,iter.max=1L,eps=1e-6,start.bw=bw.nrd, verbose=FALSE)
{#require(ks)
if(is.function(start.bw)) bw0=start.bw(x)
if(is.numeric(start.bw)) bw0=start.bw
if(is.character(start.bw)) bw0=call(start.bw, x)

Rkern=density(x,bw0,from=x[1L],to=x[1L],n=1L,give.Rkern=TRUE)

n.iter=1L
xdiff=x[1L]-x
repeat{
#### these lines are using the ks:::drvkde and or ks::kdde functions and  are replaced by explicit calculations
#        f.1=density(x,bw0,from=x[1],to=x[1],n=1)\$y
#        ddf=drvkde(x,2,bw0,se=FALSE)
#        ddf.1=approx(ddf\$x.grid[[1]],ddf\$est,xout=x[1])\$y
tmp=xdiff/bw0
f.1=mean(dnorm(tmp))/bw0
ddf.1=mean(dnorm(tmp)*(tmp*tmp-1))/bw0/bw0/bw0
bw=(f.1/ddf.1/ddf.1*Rkern/length(x))^.2
if(abs(bw-bw0)<eps || n.iter>=iter.max) return(bw)
if(verbose && isTRUE(n.iter%%verbose==0))cat(bw,fill=TRUE)
bw0=bw
n.iter=n.iter+1
}
}

if(FALSE){
f.1=kdde(x, bw0, deriv.order=0, eval.points=x[1])\$estimate
ddf.1=kdde(x, bw0, deriv.order=2, eval.points=x[1])\$estimate

locpoly(x,  drv = 0L, degree=0, kernel = "normal", gridsize=2L, range.x=0:1+x[1], bandwidth=bw0)\$y

f.1=mean(dnorm((x[1]-x)/bw0))/bw0

f.1=density(x,bw0,from=x[1],to=x[1],n=1)\$y
ddf=drvkde(x,2,bw0,se=FALSE)
ddf.1=approx(ddf\$x.grid[[1]],ddf\$est,xout=x[1])\$y
f.1;ddf.1
}
```

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MRPP documentation built on May 2, 2019, 4:46 p.m.