BIOSTATS: Likelihood Ratio Tests for Dependent Data with Applications to Functional Data Analysis

Levin Lecture Series
3:45 pm
5:00 pm
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Ana-Maria Staicu, PhD
North Carolina State University
Lecture Series
Department of Biostatistics
Open to the Public
In this talk I introduce a general inferential framework for testing hypotheses about the population mean function against semiparametric alternatives, in the context of dependent data such as functional data. The methodology is based on a pseudo likelihood approach, by treating the noise process's covariance function as an infinite-dimensional nuisance parameter and replacing it by a consistent estimator. Theoretical results for the asymptotic distribution of the pseudo likelihood ratio test are provided, and their performance is investigated numerically. The proposed methods are applied to a Sleep Health Heart Study, where the interest is testing the equality between the average normalized d-power of sleep electroencephalograms of subjects with severe sleep apnea and of matched controls.


Dept of Biostatistics