Computation of optimum Type-II progressively hybrid censoring schemes using variable neighborhood search algorithm

Ritwik Bhattacharya () and Biswabrata Pradhan ()
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Ritwik Bhattacharya: Centro de Investigación en Matemáticas (CIMAT)
Biswabrata Pradhan: Indian Statistical Institute

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2017, vol. 26, issue 4, No 10, 802-821

Abstract: Abstract Type-II progressively hybrid censoring scheme is a mixture of Type-II progressive censoring and Type-I censoring schemes. In this article, we first derive the expression of Fisher information matrix based on Type-II progressively hybrid censored data for multi-parameter distribution. We then propose a cost minimization-based optimality criterion to determine optimum Type-II progressively hybrid censoring schemes. Determination of optimum schemes through exhaustive search within the set of all admissible censoring schemes for large sample sizes is not feasible in practice. We propose a meta-heuristic algorithm based on variable neighborhood search approach for large sample sizes. A sensitivity analysis is also carried out in order to study the effect of mis-specification of parameter values or cost coefficients on the optimum solution. Finally, we also discuss A-, D- and T- optimum censoring schemes.

Keywords: Cost function; A-optimality; D-optimality; Information matrix; Variable neighborhood search algorithm; Near-optimal solution; 62N05; 90B25 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11749-017-0534-6

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