On some mixture models based on the BirnbaumSaunders distribution and associated inference
By Narayanaswamy Balakrishnan, Ramesh C. Gupta, Debasis Kundu, Víctor Leiva, Antonio Sanhueza. 2011
59 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/b4a8452762354c5f8b1c9e822725bc945f359543
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Debasis Kundu
- Carl Lee
- Felix Famoye
- Ahmad Alzaghal
- Narayanaswamy Balakrishnan
- Biswabrata Pradhan
- Gauss Moutinho Cordeiro
- Artur J. Lemonte
In Statistics and Probability
- Debasis Kundu
- Biswabrata Pradhan
- Gauss Moutinho Cordeiro
- Narayanaswamy Balakrishnan
- Felix Famoye
- Carl Lee
- Ahmad Alzaghal
- Edwin M. M. Ortega
Citations in the corpus
- Inference and optimal censoring schemes for progressively censored Birnbaum–Saunders distribution (2013, background): “For some later developments, the reader is referred to Dupis and Mills (1998), Rieck (1995, 1999), From and Li (2006), Owen (2006), Xie and Wei (2007), Ahmed et al. (2008), Balakrishnan et al. (2011) and see the references cited therein.”
- Birnbaum‐Saunders distribution: A review of models, analysis, and applications (2018, methodology): “[18] suggested the use of the EM algorithm, which can be implemented rather easily as follows.”
- Exponentiated $T$-$X$ Family of Distributions with Some Applications (2013, methodology): “Balakrishnan et al. (2011) observed that model 3 provides the best fit out of the three mixture models based on its lowest K-S statistic and highest corresponding p-value as shown in Table 5.”