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Activity Number: 377 - New Innovations and Challenges in HGLMs and H-Likelihood
Type: Invited
Date/Time: Tuesday, July 30, 2019 : 2:00 PM to 3:50 PM
Sponsor: WNAR
Abstract #307975 Presentation
Title: Analysis of Degradation Data Using Double Hierarchical Generalized Linear Model
Author(s): Maengseok Noh* and Youngjo Lee
Companies: Pukyong National University and Seoul National University
Keywords: Degradation data; Double hierarchical generalized linear models; Random effects; Outlier; Hierarchical likelihood approach

To estimate the expected lifetime of tires on a car, we use the field experiment data which report the degradation depths according to driving distance for each of four experiment cars. For analysis of data, we consider a double hierarchical generalized linear model (DHGLM) in which the mean and dispersion parameters can be modeled as random-effects models. In DHGLMs, we can allow the heterogeneity between different cars in the mean as well as the dispersion parameters. The introduction of random effects to dispersion parameters provides estimates that are less sensitive to the presence of outliers. For statistical inferences, we use the hierarchical likelihood approach. By showing various statistical tools such as model selection criteria and residual plots with real data analysis, the h-likelihood approach is very useful for degradation data.

Authors who are presenting talks have a * after their name.

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