Title: Testing lack of fit in multiple regression
Authors: Aerts, M ×
Claeskens, Gerda
Hart, JD #
Issue Date: Jun-2000
Publisher: Biometrika trust
Series Title: Biometrika vol:87 issue:2 pages:405-424
Abstract: We study lack-of-fit tests based on orthogonal series estimators. A common feature of these tests is that they are functions of score statistics that employ data-driven model dimensions. The criteria used to select the dimension are score-based versions of Are and BIC. The tests can be applied in a wide variety of settings, including both continuous and discrete data. With two or more covariates, a model sequence, i.e. a path in the alternative models space, has to be chosen. Critical points and p-values of the lack-of-fit tests can be obtained via asymptotic distribution theory or by use of the bootstrap. Data examples and a simulation study illustrate the applicability of the tests.
ISSN: 0006-3444
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
× corresponding author
# (joint) last author

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