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On modelling data from degradation sample paths over time
Author(s) -
Lin Tsung I.,
Lee Jack C.
Publication year - 2003
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/1467-842x.00282
Subject(s) - mathematics , sample (material) , statistics , data set , transformation (genetics) , maximum likelihood , linear model , degradation (telecommunications) , econometrics , computer science , biochemistry , chemistry , chromatography , gene , telecommunications
Summary This paper is mainly concerned with modelling data from degradation sample paths over time. It uses a general growth curve model with Box‐Cox transformation, random effects and ARMA( p, q ) dependence to analyse a set of such data. A maximum likelihood estimation procedure for the proposed model is derived and future values are predicted, based on the best linear unbiased prediction. The paper compares the proposed model with a nonlinear degradation model from a prediction point of view. Forecasts of failure times with various data lengths in the sample are also compared.