A Smoothing ‐based Goodness‐of‐Fit Test of Covariance for Functional Data

SummaryFunctional data methods are often applied to longitudinal data as they provide a more flexible way to capture dependence across repeated observations. However, there is no formal testing procedure to determine if functional methods are actually necessary. We propose a goodness ‐of‐fit test for comparing parametric covariance functions against general nonparametric alternatives for both irregularly observed longitudinal data and densely observed functional data. We consider a smoothing‐based test statistic and approximate its null distribution using a bootstrap proce dure. We focus on testing a quadratic polynomial covariance induced by a linear mixed effects model and the method can be used to test any smooth parametric covariance function. Performance and versatility of the proposed test is illustrated through a simulation study and three data applications. Th is article is protected by copyright. All rights reserved
Source: Biometrics - Category: Biotechnology Authors: Tags: BIOMETRIC METHODOLOGY Source Type: research