ks {ks} | R Documentation |
Kernel density estimation and kernel discriminant analysis for multivariate data (1- to 6-dimensions) with display functions.
There are three main types of functions in this package: (a) computing bandwidth selectors, (b) computing kernel estimators and (c) displaying kernel estimators.
(a) For the bandwidth matrix selectors, there are several varieties:
(i) plug-in
Hpi
, Hpi.diag
(ii) least squares (or unbiased) cross validation (LSCV or UCV)
Hlscv
, Hlscv.diag
,
(iii) biased cross validation (BCV)
Hbcv
, Hbcv.diag
and
(iv) smoothed cross validation (SCV)
Hscv
, Hscv.diag
.
The first selector in each pair is the unconstrained (or full)
selector,
and the second one is the diagonal selectors.
Scalar bandwidth selectors are not provided - see
sm
or KernSmooth
packages.
(b) For kernel density estimation, the main function is
kde
. For kernel discriminant analysis, it's kda.kde
.
(c) For display, versions of plot
, plot.kde
and
plot.kda.kde
, send to a graphics window
the results of density estimation or discriminant analysis.
For d = 1, 2, 3, 4, binned kernel estimation is available.
For an overview of this package with 2-dimensional density estimation, see
vignette("kde")
.
Tarn Duong <tduong@pasteur.fr> for most of the package. Matt Wand for the binned estimation code. Jose E. Chacon for the pilot functional estimation code.
Bowman, A. & Azzalini, A. (1997) Applied Smoothing Techniques for Data Analysis. Oxford University Press. Oxford.
Duong, T. (2004) Bandwidth Matrices for Multivariate Kernel Density Estimation. Ph.D. Thesis. University of Western Australia.
Duong, T. & Hazelton, M.L. (2003) Plug-in bandwidth matrices for bivariate kernel density estimation. Journal of Nonparametric Statistics, 15, 17-30.
Duong, T. & Hazelton, M.L. (2005) Cross-validation bandwidth matrices for multivariate kernel density estimation. Scandinavian Journal of Statistics, 32, 485-506.
Sain, S.R., Baggerly, K.A. & Scott, D.W. (1994) Cross-validation of multivariate densities. Journal of the American Statistical Association. 82, 1131-1146.
Scott, D.W. (1992) Multivariate Density Estimation: Theory, Practice, and Visualization. John Wiley & Sons. New York.
Simonoff, J. S. (1996) Smoothing Methods in Statistics. Springer-Verlag. New York.
Wand, M.P. & Jones, M.C. (1994) Multivariate plugin bandwidth selection. Computational Statistics, 9, 97-116.
Wand, M.P. & Jones, M.C. (1995) Kernel Smoothing. Chapman & Hall/CRC. London.