plot.h.ccv: Plot for Complete Cross-Validation

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

Description

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

Usage

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

Arguments

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

Author(s)

Arsalane Chouaib Guidoum [e-mail]

See Also

h.ccv.

Examples

par(mfrow=c(2,1))
plot(h.ccv(trimodal,deriv.order=0),main="")
plot(h.ccv(trimodal,deriv.order=1),main="")

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

$ccv
 [1] 0.022255581 0.019799483 0.018381299 0.017827879 0.017760842 0.017721014
 [7] 0.017417050 0.016764970 0.015810491 0.014652290 0.013396127 0.012132343
[13] 0.010927717 0.009825721 0.008850783 0.008013499 0.007315154 0.006751072
[19] 0.006312897 0.005990128 0.005771165 0.005644023 0.005596830 0.005618151
[25] 0.005697208 0.005824009 0.005989432 0.006185270 0.006404242 0.006639989
[31] 0.006887039 0.007140762 0.007397303 0.007653515 0.007906880 0.008155439
[37] 0.008397720 0.008632672 0.008859606 0.009078147 0.009288187 0.009489847
[43] 0.009683438 0.009869436 0.010048454 0.010221214 0.010388527 0.010551275
[49] 0.010710385 0.010866821

$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

$ccv
 [1] 1.89340375 1.35115808 1.17895912 1.12852721 1.02992111 0.87579582
 [7] 0.70264838 0.53983939 0.40207159 0.29292547 0.21000582 0.14878440
[13] 0.10460834 0.07344340 0.05202240 0.03778613 0.02876943 0.02348150
[19] 0.02079932 0.01988164 0.02010370 0.02100831 0.02226828 0.02365638
[25] 0.02502077 0.02626515 0.02733292 0.02819510 0.02884147 0.02927416
[31] 0.02950327 0.02954387 0.02941401 0.02913335 0.02872223 0.02820104
[37] 0.02758968 0.02690727 0.02617183 0.02540007 0.02460725 0.02380712
[43] 0.02301178 0.02223175 0.02147593 0.02075171 0.02006499 0.01942032
[49] 0.01882101 0.01826923

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