bw.boot {NPCirc} | R Documentation |
This function implements the bootstrap procedure proposed by Di Marzio et al. (2011) for selecting the smoothing parameter for density estimation taking the von Mises density as kernel.
bw.boot(x, lower=0, upper=100, np=500, tol=0.1)
x |
Data from which the smoothing parameter is to be computed. The object is coerced to class |
lower, upper |
|
np |
Number of points where to evaluate the estimator for numerical integration. Default |
tol |
Convergence tolerance for |
This method is based on the proposal of Taylor (1989) for linear data. See also Oliveira et al. (2012). The NAs will be automatically removed.
Value of the smoothing parameter.
Mar?a Oliveira, Rosa M. Crujeiras and Alberto Rodr?guez–Casal
Di Marzio, M., Panzera A. and Taylor, C.C. (2011) Kernel density estimation on the torus. Journal of Statistical Planning and Inference, 141, 2156–2173.
Oliveira, M., Crujeiras, R.M. and Rodr?guez–Casal, A. (2012) A plug–in rule for bandwidth selection in circular density. Computational Statistics and Data Analysis, 56, 3898–3908.
Taylor, C.C. (1989) Bootstrap choice of the smoothing parameter in kernel density estimation. Biometrika, 76, 705–712.
Oliveira, M., Crujeiras R.M. and Rodr?guez–Casal, A. (2014) NPCirc: an R package for nonparametric circular methods. Journal of Statistical Software, 61(9), 1–26. https://www.jstatsoft.org/v61/i09/
kern.den.circ
, bw.rt
, bw.CV
, bw.pi
set.seed(2012)
n <- 100
x <- rcircmix(n, model=17)
bw.boot(x, lower=0, upper=20)