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Birnbaum–Saunders Distribution Based on Asymmetric Heavy-Tailed Distributions, Associated Inference, and Application

Rocío Maehara et al.

Mathematical Methods of Statistics2025https://doi.org/10.3103/s1066530723600355article
ABDC B
Weight
0.37

What the paper says

Birnbaum–Saunders (BS) distribution has received considerable attention in the statistical literature, both in applied and theoretical problems. Even though much work has been done on extensions of the BS distribution, there is still a need for models for predicting extreme percentiles and for fitting data that are highly concentrated on the left-tail of the distribution. This article proposes a robust extension of the BS distribution, based on scale mixtures of skew-normal distributions that can be used to model highly asymmetric data. This extension provides flexible heavy-tailed distributions which can be used in the robust estimation of parameters in the presence of outlying observations, as well as an EM-algorithm for the maximum likelihood estimation of model parameters. Finally, the proposed model and methods of inference are examined and illustrated by means of Monte Carlo simulation studies and a real data set.

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https://doi.org/https://doi.org/10.3103/s1066530723600355

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@article{rocío2025,
  title        = {{Birnbaum–Saunders Distribution Based on Asymmetric Heavy-Tailed Distributions, Associated Inference, and Application}},
  author       = {Rocío Maehara et al.},
  journal      = {Mathematical Methods of Statistics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.3103/s1066530723600355},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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