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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/23410

Title: Shape testing in quantile varying coefficient models with heteroscedastic error
Authors: Gijbels, Irène
Ibrahim, Mohammed
Verhasselt, Anneleen
Issue Date: 2017
Citation: Journal of nonparametric statistics , 29 (2), p. 391-406
Abstract: The interest is in regression quantiles in varying coefficient models for analyzing longitudinal data. The coefficients are allowed to vary with time, and the error variance (the variability function) varies with the covariates to allow for heteroscedasticity. The functional coefficients are estimated using penalized splines (P-splines), not requiring specification of the error distribution. A likelihood-ratio-type test is considered to test the shape (constancy, monotonicity and/or convexity) of the functional coefficients. Further, testing procedures based on L1-norm, L2-norm and L∞-norm of the differences of the P-splines coefficients are considered to test for constant functional coefficients. These norm based tests perform better than the likelihood-ratio-type test in our simulation study. An extreme value test for testing monotonicity or convexity, also performs better than the likelihood-ratio-type test. The likelihood-ratio-type test is, however, useful when testing the shape of the coeffi- cients in signal and in variability function simultaneously. A real data example demonstrates the testing procedures.
Notes: Verhasselt, A (reprint author), Univ Hasselt, I Biostat, Diepenbeek, Belgium. anneleen.verhasselt@uhasselt.be
URI: http://hdl.handle.net/1942/23410
DOI: 10.1080/10485252.2017.1303066
ISI #: 000405400300012
ISSN: 1048-5252
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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