plot.h.amise: Plot for Asymptotic Mean Integrated Squared Error

In kedd: Kernel Estimator and Bandwidth Selection for Density and Its Derivatives

Description

The plot.h.amise function loops through calls to the h.amise function. Plot for asymptotic mean integrated squared error function for 1-dimensional data.

Usage

## S3 method for class 'h.amise'
plot(x, seq.bws=NULL, ...)
## S3 method for class 'h.amise'
lines(x,seq.bws=NULL, ...)

Arguments

x	object of class h.amise (output from h.amise).
seq.bws	the sequence of bandwidths in which to compute the AMISE function. By default, the procedure defines a sequence of 50 points, from 0.15*hos to 2*hos (Over-smoothing).
...	other graphics parameters, see par in package "graphics".

Value

Plot of 1-d AMISE function are sent to graphics window.

kernel	name of kernel to use.
deriv.order	the derivative order to use.
seq.bws	the sequence of bandwidths.
amise	the values of the AMISE function in the bandwidths grid.

Author(s)

Arsalane Chouaib Guidoum [e-mail]

See Also

h.amise.

Examples

plot(h.amise(bimodal,deriv.order=0))

Example output

$kernel
[1] "gaussian"

$deriv.order
[1] 0

$seq.bws
 [1] 0.09664834 0.12097479 0.14530124 0.16962769 0.19395415 0.21828060
 [7] 0.24260705 0.26693350 0.29125996 0.31558641 0.33991286 0.36423931
[13] 0.38856577 0.41289222 0.43721867 0.46154512 0.48587157 0.51019803
[19] 0.53452448 0.55885093 0.58317738 0.60750384 0.63183029 0.65615674
[25] 0.68048319 0.70480965 0.72913610 0.75346255 0.77778900 0.80211545
[31] 0.82644191 0.85076836 0.87509481 0.89942126 0.92374772 0.94807417
[37] 0.97240062 0.99672707 1.02105353 1.04537998 1.06970643 1.09403288
[43] 1.11835933 1.14268579 1.16701224 1.19133869 1.21566514 1.23999160
[49] 1.26431805 1.28864450

$amise
 [1] 0.016459273 0.013394816 0.011666164 0.010582009 0.009816736 0.009233747
 [7] 0.008772198 0.008395760 0.008078077 0.007800342 0.007550231 0.007320226
[13] 0.007105871 0.006904426 0.006713999 0.006533089 0.006360370 0.006194634
[19] 0.006034782 0.005879855 0.005729042 0.005581699 0.005437336 0.005295607
[25] 0.005156292 0.005019272 0.004884509 0.004752025 0.004621882 0.004494173
[31] 0.004369006 0.004246495 0.004126758 0.004009906 0.003896047 0.003785280
[37] 0.003677695 0.003573372 0.003472383 0.003374790 0.003280646 0.003189997
[43] 0.003102879 0.003019320 0.002939338 0.002862943 0.002790133 0.002720897
[49] 0.002655209 0.002593033

kedd documentation built on May 2, 2019, 7:32 a.m.