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A Note on Improved Approximation of the Binomial Distribution by the Skew-Normal Distribution

Author

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  • Chang, Ching-Hui
  • Lin, Jyh-Jiuan
  • Pal, Nabendu
  • Chiang, Miao-Chen

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Suggested Citation

  • Chang, Ching-Hui & Lin, Jyh-Jiuan & Pal, Nabendu & Chiang, Miao-Chen, 2008. "A Note on Improved Approximation of the Binomial Distribution by the Skew-Normal Distribution," The American Statistician, American Statistical Association, vol. 62, pages 167-170, May.
    • Handle: RePEc:bes:amstat:v:62:y:2008:m:may:p:167-170
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    Cited by:

    1. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    2. Mohammad Fraiwan Al-Saleh & Doaa Suhail Obeidat, 2022. "Approximation of the Binomial Probability Function Using the Discrete Normal Distribution," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 11(3), pages 1-32, May.
    3. Miguel A. García-Pérez, 2010. "Confidence Intervals for True Scores Using the Skew-Normal Distribution," Journal of Educational and Behavioral Statistics, , vol. 35(6), pages 762-773, December.
    4. Loperfido, Nicola, 2018. "Skewness-based projection pursuit: A computational approach," Computational Statistics & Data Analysis, Elsevier, vol. 120(C), pages 42-57.
    5. Tarpey, Thaddeus & Loperfido, Nicola, 2015. "Self-consistency and a generalized principal subspace theorem," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 27-37.
    6. Ranjani Atukorala & Maxwell L. King & Sivagowry Sriananthakumar, 2014. "Applications of Information Measures to Assess Convergence in the Central Limit Theorem," Monash Econometrics and Business Statistics Working Papers 29/14, Monash University, Department of Econometrics and Business Statistics.

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