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Pradhan, Biswabrata

Discussion of “Birnbaum-Saunders distribution: a review of models, analysis, and applications”. (English) Zbl 1428.62090

Appl. Stoch. Models Bus. Ind. 35, No. 1, 61-63 (2019).
Discussion of the paper [N. Balakrishnan and D. Kundu, ibid. 35, No. 1, 4–49 (2019; Zbl 1428.62072)].

Cited in 1 Review

MSC:

62E15 Exact distribution theory in statistics
62N05 Reliability and life testing

Keywords:

Birnbaum-Saunders distribution

Citations:

Zbl 1428.62072
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Full Text: DOI

References:

[1] Leiva V. The Birnbaum‐Saunders Distribution. New York, NY: Academic Press; 2016. · Zbl 1338.62010
[2] Rieck JR, Nedelman JR. A log‐linear model for the Birnbaum‐Saunders distribution. Technometrics. 1991; 33: 51‐ 60. · Zbl 0717.62090
[3] Leiva V, Santos‐Neto M, Cysneiros FJA, Barros M. Birnbaum‐Saunders statistical modelling: a new approach. Stat Model. 2014; 14: 21‐ 48. · Zbl 07257894
[4] Balakrishnan N, Zhu X. Inference for the Birnbaum‐Saunders lifetime regression model with applications. Commun Stat ‐ Simul Comput. 2015; 44( 8): 2073‐ 2100. · Zbl 1328.62090
[5] Saulo H, Leão J, Leiva V, Aykroyd RG. Birnbaum‐Saunders autoregressive conditional duration models applied to high‐frequency financial data. Stat Pap. 2017: 1‐ 25. https://doi.org/10.1007/s00362-017-0888-6 · Zbl 1432.62315
[6] Rahul T, Balakrishnan N, Balakrishna N. Time series with Birnbaum‐Saunders marginal distributions. Appl Stoch Model Bus Ind. 2018; 34( 4): 562‐ 581. https://doi.org/10.1002/asmb.2324 · Zbl 1400.62195
[7] Santos‐Neto M, Cysneiros FJA, Leiva V, Barros M. A reparameterized Birnbaum‐Saunders distribution and its moments, estimation and application. Revstat Stat J. 2014; 12: 247‐ 272. · Zbl 1314.62055
[8] Birnbaum ZW, Saunders SC. A new family of life distributions. J Appl Probab. 1969; 6: 319‐ 327. · Zbl 0209.49801
[9] Santos‐Neto M, Cysneiros FJA, Leiva V, Barros M. Reparameterized Birnbaum‐Saunders regression models with varying precision. Electron J Stat. 2016; 10: 2825‐ 2855. · Zbl 1348.62220
[10] R‐Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2018.
[11] Stasinopoulos D, Rigby R. Generalized additive models for location, scale and shape (GAMLSS) in R. J Stat Softw. 2008; 23: 1‐ 46.
[12] Benjamin MA, Rigby RA, Stasinopoulos DM. Generalized autoregressive moving average models. J Am Stat Assoc. 2003; 98: 214‐ 223. · Zbl 1047.62076
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