Exact inference for two exponential populations with competing risks data  

Exact inference for two exponential populations with competing risks data

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作  者:Song Mao Yimin Shi Liang Wang 

机构地区:[1]School of Applied Mathematics,Northwestern Polytechnical University [2]School of Mathematics,Xidian University

出  处:《Journal of Systems Engineering and Electronics》2014年第4期711-720,共10页系统工程与电子技术(英文版)

基  金:supported by the National Natural Science Foundation of China(71171164)

摘  要:In a reliability comparative test, the joint censoring model is usually adopted to evaluate the performances of units with the same facility. However, most researchers ignore the pos- sibility that there is more than one factor for the failure when a test unit fails. To solve this problem, we consider a joint Type-II hybrid censoring model for the analysis of exponential competing failure data. Based on the maximum likelihood theory, we compute the maximum likelihood estimators (MLEs) of parameters and then obtain the condition ensuring MLEs existence for every unknown parameter. Then we derive the conditional exact distributions and corresponding moment properties for parameters by the moment generating function (MGF). A Monte-Carlo simulation is conducted to compare the performances of different ways. And finally, we conduct a numerical example to illustrate the proposed method.In a reliability comparative test, the joint censoring model is usually adopted to evaluate the performances of units with the same facility. However, most researchers ignore the pos- sibility that there is more than one factor for the failure when a test unit fails. To solve this problem, we consider a joint Type-II hybrid censoring model for the analysis of exponential competing failure data. Based on the maximum likelihood theory, we compute the maximum likelihood estimators (MLEs) of parameters and then obtain the condition ensuring MLEs existence for every unknown parameter. Then we derive the conditional exact distributions and corresponding moment properties for parameters by the moment generating function (MGF). A Monte-Carlo simulation is conducted to compare the performances of different ways. And finally, we conduct a numerical example to illustrate the proposed method.

关 键 词:joint Type-II hybrid censoring competing causes mo-ment generating function likelihood inference exponential distri-bution. 

分 类 号:O212.1[理学—概率论与数理统计]

 

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