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

Ritwik Bhattacharya ^[2] ; Biswabrata Pradhan ^[1]
1. [1] Indian Statistical Institute
  
  Indian Statistical Institute
  
  India
2. [2] Centro de Investigación en Matemáticas (CIMAT)
Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 26, Nº. 4, 2017, págs. 802-821
Idioma: inglés
DOI: 10.1007/s11749-017-0534-6
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Resumen
- 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.