Filtered kernel density estimation

@misc{citeulike:1669358, abstract = {this paper for the construction of the filtering functions for two reasons: we have some experience in finite mixture estimation, and it is a convenient arena in which to do some comparisons with the standard kernel estimator. There are a number of methods for choosing the number of components to be used, either subjectively or using automated methods such as in Priebe 1994, Solka et al 1995 or Rogers et al 1995. In this paper, we will either assume knowledge of the true mixture (for comparison ...}, author = {Marchette, D. and Priebe, C. and Rogers, G. and Solka, J. }, citeulike-article-id = {1669358}, keywords = {bandwidth, density, kernel}, posted-at = {2007-09-18 15:22:57}, priority = {0}, title = {Filtered kernel density estimation}, url = {http://citeseer.ist.psu.edu/marchette95filtered.html}, year = {1995} }

TY - GEN ID - citeulike:1669358 L3 - citeulike-article-id:1669358 N2 - this paper for the construction of the filtering functions for two reasons: we have some experience in finite mixture estimation, and it is a convenient arena in which to do some comparisons with the standard kernel estimator. There are a number of methods for choosing the number of components to be used, either subjectively or using automated methods such as in Priebe 1994, Solka et al 1995 or Rogers et al 1995. In this paper, we will either assume knowledge of the true mixture (for comparison ... TI - Filtered kernel density estimation KW - bandwidth KW - density KW - kernel AU - Marchette, D AU - Priebe, C AU - Rogers, G AU - Solka, J PY - 1995/// UR - http://citeseer.ist.psu.edu/marchette95filtered.html ER -