A Smoothing-Based Goodness-of-Fit Test of Covariance for Functional Data

Biometrics - Tập 75 Số 2 - Trang 562-571 - 2019
Stephanie T. Chen1,1,2, Luo Xiao1, Ana‐Maria Staicu1
1Department of Statistics, North Carolina State University, Raleigh, North Carolina
2Stephanie T. Chen,

Tóm tắt

Abstract Functional 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 procedure. 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.

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Biometrics

Tập 75 Số 2

562-571

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