Statistical Inference on the Basis of Sequential Order Statistics under a Linear Trend for Conditional Proportional Hazard Rates

  • Majid Hashempour Department of Statistics‎, ‎School of Science, University of Hormozgan‎, ‎Bandar Abbas, Iran
  • Mahdi Doostparast Department of Statistics‎, ‎School of‎ ‎Mathematical Sciences, Ferdowsi University of Mashhad‎, ‎Mashhad,Iran
  • Zohreh Pakdaman
DOI: https://doi.org/10.19139/soic-2310-5070-802
Keywords: ‎Dynamic systems, Linear trend model, Exponential distribution, Hazard function

Abstract

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.

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Published
2020-05-28
How to Cite
Hashempour, M., Doostparast, M., & Pakdaman, Z. (2020). Statistical Inference on the Basis of Sequential Order Statistics under a Linear Trend for Conditional Proportional Hazard Rates. Statistics, Optimization & Information Computing, 8(2), 462-470. https://doi.org/10.19139/soic-2310-5070-802
Issue
Vol 8 No 2 (2020)
Section
Research Articles
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