being smoothed by kernel functions, a technique known as double smoothing. Experimental studies show that the new mixture … models and double smoothing. …

In this paper a modified double smoothing bandwidth selector, MDS, based on a new criterion, which combines the plug …-in and the double smoothing ideas, is proposed. A self-complete iterative double smoothing rule (_IDS ) is introduced as a …

selector performs very well, and it performs uniformly better than a double smoothing bandwidth selector using a difference …A bandwidth selector for local polynomial fitting is proposed following the bootstrap idea, which is just a double … smoothing bandwidth selector with a bootstrap variance estimator, defined as the mean squared residuals of a pilot estimate. No …

selector performs very well, and it performs uniformly better than a double smoothing bandwidth selector using a difference …A bandwidth selector for local polynomial fitting is proposed following the bootstrap idea, which is just a double … smoothing bandwidth selector with a bootstrap variance estimator, defined as the mean squared residuals of a pilot estimate. No …

selector performs very well, and it performs uniformly better than a double smoothing bandwidth selector using a difference …A bandwidth selector for local polynomial fitting is proposed following the bootstrap idea, which is just a double … smoothing bandwidth selector with a bootstrap variance estimator, defined as the mean squared residuals of a pilot estimate. No …

The problem of selecting bandwidth for nonparametric regression is investigated. The methodology used here is a double-smoothing …

The problem of selecting bandwidth for nonparametric regression is investigated. The methodology used here is a double-smoothing …

The problem of selecting bandwidth for nonparametric regression is investigated. The methodology used here is a double-smoothing …