| bw.CDF.pi {sROC} | R Documentation |
Plug-in bandwidth selectors for kernel CDF estimation using Altman and Leger's approach.
bw.CDF.pi(x, pilot="UCV")
x |
numeric vector. |
pilot |
a character string giving a rule to choose the pilot bandwidth to estimate E(f''(x)). There are 6 choices: The default, “ucv”, implement unbiased cross-validation, “nrd0” is the Silverman's rule of thumb, “nrd” is the Scott's method (1992), “bcv” is the biased cross-validation, “sj” is the method of Sheather and Jones (1991), “onestage” is the one-stage method by Wand and Jones. |
bw.CDF implements a rule-of-thumb for choosing the bandwidth of a Gaussian kernel CDF estimator.
A bandwidth on a scale suitable for the bw argument of kCDF.
X.F. Wang wangx6@ccf.org
Altman, N., and Leger, C. (1995). Bandwidth selection for kernel distribution function estimation. Journal of Statistical Planning and Inference, 46, 195-214.
Scott, D. W. (1992) Multivariate Density Estimation: Theory, Practice, and Visualization. Wiley.
Sheather, S. J. and Jones, M. C. (1991). A reliable data-based bandwidth selection method for kernel density estimation. Journal of Royal Statistical Society Series B, 53, 683-690.
Silverman, B. W. (1986) Density Estimation. London: Chapman and Hall.
Wand, M.P. and Jones, M.C. (1995) Kernel Smoothing. New York: Chapmon and Hall.
set.seed(100) n <- 200 x <- c(rnorm(n/2, mean=-2, sd=1), rnorm(n/2, mean=3, sd=0.8)) bw.CDF.pi(x) bw.CDF.pi(x, pilot="nrd0") bw.CDF.pi(x, pilot="nrd") bw.CDF.pi(x, pilot="bcv") bw.CDF.pi(x, pilot="sj") bw.CDF.pi(x, pilot="onestage")