Open AccessStatistical Inference on the Basis of Sequential Order Statistics under a Linear Trend for Conditional Proportional Hazard Rates
Author(s) -
Majid Hashempour,
Mahdi Doostparast,
Zohreh Pakdaman
Publication year - 2020
Publication title -
statistics, optimization and information computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.297
H-Index - 12
eISSN - 2311-004X
pISSN - 2310-5070
DOI - 10.19139/soic-2310-5070-802
Subject(s) - mathematics , homogeneity (statistics) , statistics , inference , statistical inference , fisher information , order statistic , basis (linear algebra) , exponential function , hazard , computer science , mathematical analysis , geometry , artificial intelligence , chemistry , organic chemistry
This paper deals with systems consisting of independent and heterogeneous exponential components. Since failures of components may change lifetimes of surviving components because of load sharing, a linear trend for conditionally proportional hazard rates is considered. Estimates of parameters, both point and interval estimates, are derived on the basis of observed component failures for s(≥ 2) systems. Fisher information matrix of the available data is also obtained which can be used for studying asymptotic behaviour of estimates. The generalized likelihood ratio test is implemented for testing homogeneity of s systems. Illustrative examples are also given.