Skip to main content
Article
Statistical Methods for Degradation Data With Dynamic Covariates Information and an Application to Outdoor Weathering Data
Technometrics
  • Yili Hong, Virginia Tech
  • Yuanyuan Duan, Virginia Tech
  • William Q. Meeker, Iowa State University
  • Deborah L. Stanley, National Institute of Standards and Technology
  • Xiaohong Gu, National Institute of Standards and Technology
Document Type
Article
Publication Version
Published Version
Publication Date
5-1-2015
DOI
10.1080/00401706.2014.915891
Abstract

Degradation data provide a useful resource for obtaining reliability information for some highly reliable products and systems. In addition to product/system degradation measurements, it is common nowadays to dynamically record product/system usage as well as other life-affecting environmental variables, such as load, amount of use, temperature, and humidity. We refer to these variables as dynamic covariate information. In this article, we introduce a class of models for analyzing degradation data with dynamic covariate information. We use a general path model with individual random effects to describe degradation paths and a vector time series model to describe the covariate process. Shape-restricted splines are used to estimate the effects of dynamic covariates on the degradation process. The unknown parameters in the degradation data model and the covariate process model are estimated by using maximum likelihood. We also describe algorithms for computing an estimate of the lifetime distribution induced by the proposed degradation path model. The proposed methods are illustrated with an application for predicting the life of an organic coating in a complicated dynamic environment (i.e., changing UV spectrum and intensity, temperature, and humidity). This article has supplementary material online.

Comments

This is an article published by Taylor & Francis as Hong, Yili, Yuanyuan Duan, William Q. Meeker, Deborah L. Stanley, and Xiaohong Gu. "Statistical methods for degradation data with dynamic covariates information and an application to outdoor weathering data." Technometrics 57, no. 2 (2015): 180-193. DOI: 10.1080/00401706.2014.915891.

Rights
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.
Language
en
File Format
application/pdf
Citation Information
Yili Hong, Yuanyuan Duan, William Q. Meeker, Deborah L. Stanley, et al.. "Statistical Methods for Degradation Data With Dynamic Covariates Information and an Application to Outdoor Weathering Data" Technometrics Vol. 57 Iss. 2 (2015) p. 180 - 193
Available at: http://works.bepress.com/wqmeeker/153/