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)Value of the smoothing parameter.
Data from which the smoothing parameter is to be computed. The object is coerced to class circular.
lower and upper boundary of the interval to be used in the search for the value of the smoothing parameter. Default
lower=0 and upper=100.
Number of points where to evaluate the estimator for numerical integration. Default np=500.
Convergence tolerance for optimize.
Maria Oliveira, Rosa M. Crujeiras and Alberto Rodriguez--Casal
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.
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 Rodriguez--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 Rodriguez--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)
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