On the survival models for step-stress experiments based on fuzzy life time data

Muhammad Shafiq () and Muhammad Atif ()
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Muhammad Shafiq: Vienna University of Technology
Muhammad Atif: University of Peshawar

Quality & Quantity: International Journal of Methodology, 2017, vol. 51, issue 1, No 6, 79-91

Abstract: Abstract In statistical methodologies of life time analyses accelerated life testing (ALT) has a significant importance. In accelerated life testing the measurements of life times are recorded under various conditions which are more severe than usual environment. The techniques related to the inference of life times in ALT are usually based on precise measurements. In practical applications life time data have two types of uncertainty, one is stochastic variation and the other is fuzziness. Classical stochastic models are developed to draw inference based on the variation among observations, and do nothing with fuzziness. By doing so the analyses are based on incomplete information and can lead to misleading conclusions. In this study estimators are proposed to cover fuzziness in addition to stochastic variation of the life times. The results based on the proposed methods are more suitable for realistic life time data.

Keywords: Accelerated life testing; Fuzzy number; Hazard function; Life time; Non-precise data (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11135-015-0295-9

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