bwadap.numeric: Adaptive bandwidth choice for infinite order density...
In iosmooth: Functions for Smoothing with Infinite Order Flat-Top Kernels

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/bwadap.R

Adaptive bandwidth choice for infinite order flat-top kernel density estimates.

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## S3 method for class 'numeric'
bwadap(x, smax = 13.49/IQR(x), n.points = 1000, Kn = 1.349 * 
    5/IQR(x), c.thresh = 2, ...)

`x`	A univariate data set.
`smax`	The algorithm searches for smoothing parameters on the interval `[0, smax]`. `smax` is problem dependent, and the defaults are not consistently appropriate.
`n.points`	The number of points in `[0, smax]` at which the algorithm looks for crossing of the threshold `c.thresh*sqrt(log(n,10)/n)`. If the sample characteristic function is highly oscillatory on `[0,smax]`, this may need to be increased.
`Kn`	Tuning parameter `Kn` discussed in Politis (2003). Roughly, the distance over which the sample characteristic function must stay below the threshold determined by `c.thresh`.
`c.thresh`	The bandwidth is chosen by looking for the first time the sample characteristic function drops below `c.thresh*sqrt(log(n,10)/n)` and stays below that level for a distance of `Kn`.
`...`	Currently unimplemented.

Returns a bandwidth, h, for use with infinite order flat-top kernel density estimates. All frequencies higher than 1/h are downweighted by the kernel. All kernels in this package are scaled to use roughly the same bandwidth. We recommend using this algorithm in conjunction with bwplot.numeric to double check the automated selection.

Returns the estimated kernel bandwidth h.

Timothy L. McMurry

Politis, D. N. (2003). Adaptive bandwidth choice. Journal of Nonparametric Statistics, 15(4-5), 517-533.

bwadap, bwadap.ts, bwplot.numeric, bwplot

x <- rnorm(100)
bwplot(x)
h <- bwadap(x)
plot(iodensity(x, h, kernel="Trap"), type="l")
rug(x)
# Add the truth in red
xs <- seq(-3, 3, len=1000)
lines(xs, dnorm(xs), col="red")