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Exact test of goodness of fit for binomial distribution

Author

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  • Benchong Li

    (Xidian University)

  • Liya Fu

    (Xi’an Jiaotong University)

Abstract

In this paper, we consider an exact test of goodness of fit for binomial distribution in sparse data situation. A conventional way is viewing this problem as an independence test problem of a two-way contingency table. We propose an approach to promote the efficiency of the Diaconis–Sturmfels (DS) algorithm when n (sample size) is much larger than m [the first parameter of a binomial distribution B(m, p)] through representing the data and then utilizing minimal Markov bases of the corresponding multinomial model. Simulation results and real data analysis indicate that our method makes the DS algorithm computationally faster.

Suggested Citation

  • Benchong Li & Liya Fu, 2018. "Exact test of goodness of fit for binomial distribution," Statistical Papers, Springer, vol. 59(3), pages 851-860, September.
  • Handle: RePEc:spr:stpapr:v:59:y:2018:i:3:d:10.1007_s00362-016-0793-4
    DOI: 10.1007/s00362-016-0793-4
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    References listed on IDEAS

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    1. Sangun Park & Johan Lim, 2015. "On censored cumulative residual Kullback–Leibler information and goodness-of-fit test with type II censored data," Statistical Papers, Springer, vol. 56(1), pages 247-256, February.
    2. Roberto Quinino & Linda Ho & Emílio Suyama, 2013. "Alternative estimator for the parameters of a mixture of two binomial distributions," Statistical Papers, Springer, vol. 54(1), pages 47-69, February.
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    4. V. Zardasht & S. Parsi & M. Mousazadeh, 2015. "On empirical cumulative residual entropy and a goodness-of-fit test for exponentiality," Statistical Papers, Springer, vol. 56(3), pages 677-688, August.
    5. Hara, Hisayuki & Takemura, Akimichi & Yoshida, Ruriko, 2010. "On connectivity of fibers with positive marginals in multiple logistic regression," Journal of Multivariate Analysis, Elsevier, vol. 101(4), pages 909-925, April.
    6. W. M. Patefield, 1981. "An Efficient Method of Generating Random R × C Tables with Given Row and Column Totals," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 30(1), pages 91-97, March.
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    Cited by:

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