Computational Statistics & Data Analysis
An assessment of finite sample performance of adaptive methods in density estimation
Computational Statistics & Data Analysis
Estimation of densities and derivatives of densities with directional data
Journal of Multivariate Analysis
Fitting mixtures of von mises distributions: a case study involving sudden infant death syndrome
Computational Statistics & Data Analysis
Clustering on the Unit Hypersphere using von Mises-Fisher Distributions
The Journal of Machine Learning Research
Contribution to the bandwidth choice for kernel density estimates
Computational Statistics
Automatic bandwidth selection for circular density estimation
Computational Statistics & Data Analysis
A data-based algorithm for choosing the window width when estimating the density at a point
Computational Statistics & Data Analysis
Kernel density estimation for directional-linear data
Journal of Multivariate Analysis
A Bayesian model for longitudinal circular data based on the projected normal distribution
Computational Statistics & Data Analysis
| Hi-index | 0.03 |
A new plug-in rule procedure for bandwidth selection in kernel circular density estimation is introduced. The performance of this proposal is checked throughout a simulation study considering a variety of circular distributions exhibiting multimodality, peakedness and/or skewness. The plug-in rule behavior is also compared with other existing bandwidth selectors. The method is illustrated with some classical datasets.