Genetic algorithm approach with an adaptive search space based on EM algorithm in two-component mixture Weibull parameter estimation

DOI10.1007/s00180-020-01044-5zbMath1505.62223OpenAlexW3103930807MaRDI QIDQ2032219

Yusuf Şahin, Melih Burak Koca, Muhammet Burak Kılıç

Publication date: 16 June 2021

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-020-01044-5

zbMATH Keywords

Weibull distributionbootstrap percentile intervalfinite mixture distributions

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Point estimation (62F10) Approximation methods and heuristics in mathematical programming (90C59)

Uses Software

• Matlab
• R
• Maxlik
• GA
• extWeibQuant
• maxLik
• bootstrap

Cites Work

• Optimization by Simulated Annealing
• A new approach for parameter estimation of finite Weibull mixture distributions for reliability modeling
• Comparison of certain value-at-risk estimation methods for the two-parameter Weibull loss distribution
• A genetic algorithm for designing microarray experiments
• Estimating the parameters of Weibull distribution using simulated annealing algorithm
• A genetic algorithm for the vehicle routing problem
• maxLik: a package for maximum likelihood estimation in R
• Practical Genetic Algorithms
• Heterogeneous data modeling with two-component Weibull–Poisson distribution
• A comparison of the parameter estimation methods for bimodal mixture Weibull distribution with complete data
• Modelling claim number using a new mixture model: negative binomial gamma distribution
• Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes
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