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http://dx.doi.org/10.5351/CSAM.2016.23.1.033

Variance components estimation in the presence of drift  

Kim, Jaehee (Department of Statistics, Duksung Women's University)
Ogden, Todd (Department of Biostatistics, Columbia University)
Publication Information
Communications for Statistical Applications and Methods / v.23, no.1, 2016 , pp. 33-45 More about this Journal
Abstract
Variance components should be estimated based on mean change when the mean of the observations drift gradually over time. Consistent estimators for the variance components are studied for a particular modeling situation with some underlying functions or drift. We propose a new variance estimator with Fourier estimation of variations. The consistency of the proposed estimator is proved asymptotically. The proposed procedures are studied and compared empirically with the variance estimators removing trends. The result shows that our variance estimator has a smaller mean square error and depends on drift patterns. We estimate and apply the variance to Nile River flow data and resting state fMRI data.
Keywords
fMRI data; fourier series; pseudoresiduals; m-dependent data; slowly varying functions;
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