
Accession Number : ADA119915
Title : Statistical Modeling of Bivariate Data.
Descriptive Note : Technical rept.,
Corporate Author : TEXAS A AND M UNIV COLLEGE STATION INST OF STATISTICS
Personal Author(s) : Woodfield,Terry Joe
PDF Url : ADA119915
Report Date : Aug 1982
Pagination or Media Count : 271
Abstract : A technique for modeling bivariate data that is based on the theory of orthogonal expansions in a separable Hilbert space is examined. A new nonparametric density estimation procedure is developed using an information criterion and is shown to be equivalent to least squares estimation of a density when the criterion function is computed with respect to the empirical distribution function. Computer programs are presented that implement the procedure for the univariate and bivariate cases. Examples utilizing these programs are given and comparisons made to existing density estimation techniques. (Author)
Descriptors : *Bivariate analysis, *Bivariate density functions, *Mathematical models, *Statistical analysis, Orthogonality, Expansion, Hilbert space, Separation, Nonparametric statistics, Least squares method, Estimates, Entropy, Distribution functions, Computer programs, Theses
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE