Abstract
Four powerful generalizations of the usual local polynomial nonparametric regression methodology are (a) local polynomial methods in generalized linear models; (b) varying coefficient generalized linear models, where the possibly multivariate coefficients in a generalized linear model are estimated nonparametrically; (c) local likelihood methods; and (d) local estimating equations, which generalize nonparametric regression to the estimating equation context. We construct bootstrap confidence intervals for the nonparametrically estimated functions in all four contexts.
Item Type: | Paper |
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Faculties: | Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386 Special Research Fields > Special Research Field 386 |
Subjects: | 500 Science > 510 Mathematics |
URN: | urn:nbn:de:bvb:19-epub-1595-4 |
Language: | English |
Item ID: | 1595 |
Date Deposited: | 05. Apr 2007 |
Last Modified: | 04. Nov 2020, 12:45 |