Bayes least squares linear estimation of densities

Autor:	H. D. Brunk, John Shin
Rok vydání:	1984
Předmět:	Statistics and Probability Iteratively reweighted least squares Non-linear least squares Linear predictor function Linear regression Statistics Applied mathematics Generalized least squares Total least squares Least squares Linear least squares Mathematics
Zdroj:	Communications in Statistics - Theory and Methods. 13:2253-2291
ISSN:	1532-415X 0361-0926
DOI:	10.1080/03610928408828825
Popis:	Linear, least squares statistical methods in which the "parameters" are interpreted as random variables were introduced by Whittle, and further developed by Hartigan and others. They are applied here to the problem of estimating the coefficients in an orthogonal expansion of a multivariate density, given a simple random sample.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::f2b1119f55ba83b1aabfde45cd4b2e5c https://doi.org/10.1080/03610928408828825 Zobrazit plný text záznamu