ks (version 1.5.7)

ks: ks

Description

Kernel density estimation and kernel discriminant analysis for multivariate data (1- to 6-dimensions) with display functions.

Details

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. A scalar plug-in bandwidth selectors is implemented as hpi. The code is taken from the dpik selector in the KernSmooth package. (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").

References

Bowman, A. & Azzalini, A. (1997) Applied Smoothing Techniques for Data Analysis. Oxford University Press. Oxford.

Chac'on, J.E. & Duong, T. (2008) Multivariate plug-in bandwidth selection with unconstrained pilot matrices. Submitted. 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.

Silverman, B. (1986) Density Estimation for Statistics and Data Analysis. Chapman & Hall/CRC. London.

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.

See Also

sm, KernSmooth