Some studies of the bootstrap have assessed the effect of smoothing the estimated distribution that is resampled, a process usually known as the smoothed bootstrap. Generally, the smoothed ...

A kernel estimator uses an explicitly defined set of weights at each point x to produce the estimate at x. The kernel estimator of f has the form where W is the weight function that depends on the ...

The problem of selecting the bandwidth of a kernel regression estimator when the observed data are serially correlated is considered. The bandwidth is selected by using a version of cross-validation ...

Please note that these resources are for demonstration purposes only; the eBook project explored a variety of media to document statistical resources and render aspects of them interactive, but these ...

A kernel estimator uses an explicitly defined set of weights at each point x to produce the estimate at x. The kernel estimator of f has the form where W is the weight function that depends on the ...

Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed data, ...