A brief survey of bandwidth selection for density estimation

There has been major progress in recent years in data-based bandwidth selection for kernel density estimation. Some ''second generation'' methods, including plug-in and smoothed bootstrap techniques, have been developed that are far superior to well-known ''first generation'' methods, such as rules of thumb, least squares cross-validation, and biased cross-validation. We recommend a ''solve-the-equation'' plug-in bandwidth selector as being most reliable in terms of overall performance. This article is intended to provide easy accessibility to the main ideas for nonexperts.