出版日期：2018-10-08 00:00:00

著者：J-Y Chiang; S Wang; T-R Tsai; T Li

著錄名稱、卷期、頁數：Mathematical Problems in Engineering 2018, 3465909 (29 pages)

摘要：This paper studies a discriminant problem of location-scale family in case of prediction from type II censored samples. Three model selection approaches and two types of predictors are, respectively, proposed to predict the future order statistics from censored data when the best underlying distribution is not clear with several candidates. Two members in the location-scale family, the normal distribution and smallest extreme value distribution, are used as candidates to illustrate the best model competition for the underlying distribution via using the proposed prediction methods. The performance of correct and incorrect selections under correct specification and misspecification is evaluated via using Monte Carlo simulations. Simulation results show that model misspecification has impact on the prediction precision and the proposed three model selection approaches perform well when more than one candidate distributions are competing for the best underlying distribution. Finally, the proposed approaches are applied to three data sets.

語言：en_US

ISSN：1563-5147

期刊性質：國外

收錄於：SCI Scopus

審稿制度：是

國別：GBR

出版型式：電子版,紙本