On modelling data from degradation sample paths over time
| dc.citation.epage | 270 | en_US |
| dc.citation.issue | 3 | en_US |
| dc.citation.spage | 257 | en_US |
| dc.citation.volume | 45 | en_US |
| dc.citation.woscount | 11 | |
| dc.contributor.author | Lin, TI | en_US |
| dc.contributor.author | Lee, JC | en_US |
| dc.contributor.department | 統計學研究所 | zh_TW |
| dc.contributor.department | 資訊管理與財務金融系 註：原資管所+財金所 | zh_TW |
| dc.contributor.department | Institute of Statistics | en_US |
| dc.contributor.department | Department of Information Management and Finance | en_US |
| dc.date.accessioned | 2014-12-08T15:40:21Z | |
| dc.date.available | 2014-12-08T15:40:21Z | |
| dc.date.issued | 2003-09-01 | en_US |
| dc.description.abstract | 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. | en_US |
| dc.identifier.issn | 1369-1473 | en_US |
| dc.identifier.journal | AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/27547 | |
| dc.identifier.wosnumber | WOS:000184955400001 | |
| dc.language.iso | en_US | en_US |
| dc.subject | ARMA(p, q) dependence | en_US |
| dc.subject | Box-Cox transformation | en_US |
| dc.subject | ECME | en_US |
| dc.subject | maximum likelihood estimation | en_US |
| dc.subject | semi-variogram | en_US |
| dc.title | On modelling data from degradation sample paths over time | en_US |
| dc.type | Article | en_US |