plot.h.bcv: Plot for Biased Cross-Validation

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

Description

The plot.h.bcv function loops through calls to the h.bcv function. Plot for biased cross-validation function for 1-dimensional data.

Usage

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

Arguments

x	object of class h.bcv (output from h.bcv).
seq.bws	the sequence of bandwidths in which to compute the biased cross-validation 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 biased cross-validation 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.
bcv	the values of the biased cross-validation function in the bandwidths grid.

Author(s)

Arsalane Chouaib Guidoum [e-mail]

See Also

h.bcv.

Examples

## EXAMPLE 1:

plot(h.bcv(trimodal, whichbcv = 1, deriv.order = 0),main="",sub="")
lines(h.bcv(trimodal, whichbcv = 2, deriv.order = 0),col="red")
legend("topright", c("BCV1","BCV2"),lty=1,col=c("black","red"),inset = .015)

## EXAMPLE 2:

plot(h.bcv(trimodal, whichbcv = 1, deriv.order = 1),main="",sub="")
lines(h.bcv(trimodal, whichbcv = 2, deriv.order = 1),col="red")
legend("topright", c("BCV1","BCV2"),lty=1,col=c("black","red"),inset = .015)

Example output

$kernel
[1] "gaussian"

$deriv.order
[1] 0

$seq.bws
 [1] 0.07221601 0.09039282 0.10856964 0.12674646 0.14492328 0.16310010
 [7] 0.18127691 0.19945373 0.21763055 0.23580737 0.25398419 0.27216100
[13] 0.29033782 0.30851464 0.32669146 0.34486828 0.36304509 0.38122191
[19] 0.39939873 0.41757555 0.43575237 0.45392918 0.47210600 0.49028282
[25] 0.50845964 0.52663646 0.54481327 0.56299009 0.58116691 0.59934373
[31] 0.61752054 0.63569736 0.65387418 0.67205100 0.69022782 0.70840463
[37] 0.72658145 0.74475827 0.76293509 0.78111191 0.79928872 0.81746554
[43] 0.83564236 0.85381918 0.87199600 0.89017281 0.90834963 0.92652645
[49] 0.94470327 0.96288009

$bcv
 [1] 0.020978010 0.017576162 0.015546542 0.014084318 0.012785614 0.011536567
 [7] 0.010345315 0.009249289 0.008277507 0.007441951 0.006741247 0.006166364
[13] 0.005704633 0.005342032 0.005064462 0.004858477 0.004711664 0.004612821
[19] 0.004552042 0.004520741 0.004511636 0.004518699 0.004537046 0.004562811
[25] 0.004593002 0.004625356 0.004658220 0.004690433 0.004721249 0.004750257
[31] 0.004777322 0.004802541 0.004826195 0.004848714 0.004870637 0.004892589
[37] 0.004915240 0.004939289 0.004965434 0.004994351 0.005026681 0.005063011
[43] 0.005103865 0.005149696 0.005200882 0.005257719 0.005320425 0.005389140
[49] 0.005463928 0.005544784

$kernel
[1] "gaussian"

$deriv.order
[1] 1

$seq.bws
 [1] 0.09967698 0.12476575 0.14985451 0.17494328 0.20003204 0.22512081
 [7] 0.25020957 0.27529834 0.30038710 0.32547587 0.35056463 0.37565339
[13] 0.40074216 0.42583092 0.45091969 0.47600845 0.50109722 0.52618598
[19] 0.55127475 0.57636351 0.60145228 0.62654104 0.65162981 0.67671857
[25] 0.70180734 0.72689610 0.75198486 0.77707363 0.80216239 0.82725116
[31] 0.85233992 0.87742869 0.90251745 0.92760622 0.95269498 0.97778375
[37] 1.00287251 1.02796128 1.05305004 1.07813880 1.10322757 1.12831633
[43] 1.15340510 1.17849386 1.20358263 1.22867139 1.25376016 1.27884892
[49] 1.30393769 1.32902645

$bcv
 [1] 1.006339007 0.675963333 0.500966550 0.361417323 0.250314674 0.168725911
 [7] 0.112391146 0.074843963 0.050379302 0.034761888 0.025025392 0.019142371
[13] 0.015739027 0.013885358 0.012956626 0.012542860 0.012384905 0.012326313
[19] 0.012277535 0.012190768 0.012043450 0.011828053 0.011545999 0.011204051
[25] 0.010812087 0.010381645 0.009924873 0.009453763 0.008979565 0.008512376
[31] 0.008060871 0.007632158 0.007231745 0.006863589 0.006530212 0.006232857
[37] 0.005971667 0.005745875 0.005553992 0.005393980 0.005263413 0.005159616
[43] 0.005079781 0.005021066 0.004980670 0.004955896 0.004944193 0.004943185
[49] 0.004950692 0.004964740

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