Warranty Claim Forecasting Based On Weighted Maximum Likelihood Estimation

被引:18
作者
Akbarov, Artur [1 ]
Wu, Shaomin [1 ]
机构
[1] Cranfield Univ, Sch Appl Sci, Cranfield MK43 0AL, Beds, England
基金
英国工程与自然科学研究理事会;
关键词
warranty forecasting; Poisson processes; weighted maximum likelihood method; overdispersion; PREDICTION; MODEL;
D O I
10.1002/qre.1399
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Warranty claims reported in recent months might carry more up to date information than those reported in earlier months. Using weighted maximum likelihood estimation for estimating model parameters might therefore lead to better performance of warranty forecasting models than maximum likelihood estimation. This paper examines this issue and also presents comparison of the forecasting performance of the parametric models such as Poisson processes and ARIMA models and non parametric models such as artificial neural networks. It shows that mixed non homogenous Poisson process models can lead to better forecasting results than other competing methods. The paper also shows that the models built with the weighted maximum likelihood estimation yield smaller error than those based on the maximum likelihood estimation. Copyright (C) 2012 John Wiley & Sons, Ltd.
引用
收藏
页码:663 / 669
页数:7
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