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Maximum precision estimation for a step-stress model using two-stage methodologies

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  • Sudeep R. Bapat
  • Yan Zhuang

Abstract

In this paper, we consider a two-stage sequential estimation procedure to estimate the parameters of a cumulative exposure model under an accelerated testing scenario. In particular, we focus on a step-stress model where the stress level changes after a pre-specified number of failures occur, which is also random. This is termed as a ‘random stress change time’ in the literature. We further aim to estimate these parameters using maximum precision and hence use a certain variance optimality criteria. Our proposed two-stage estimation procedures follow interesting efficiency properties and their applicability is seen through extensive simulation analyses and a pseudo-real data example from reliability studies.

Suggested Citation

  • Sudeep R. Bapat & Yan Zhuang, 2022. "Maximum precision estimation for a step-stress model using two-stage methodologies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(13), pages 3344-3360, October.
    • Handle: RePEc:taf:japsta:v:49:y:2022:i:13:p:3344-3360
    DOI: 10.1080/02664763.2021.1944997
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