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Small Sample Comparison of Different Estimators of Negative Binomial Parameters

E. P. Pieters, C. E. Gates, J. H. Matis and W. L. Sterling
Biometrics
Vol. 33, No. 4 (Dec., 1977), pp. 718-723
DOI: 10.2307/2529470
Stable URL: http://www.jstor.org/stable/2529470
Page Count: 6
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Small Sample Comparison of Different Estimators of Negative Binomial Parameters
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Abstract

Four methods of estimating the negative binomial parameters from small samples were examined: moment, maximum likelihood (ML), digamma and zero-class estimators. The latter two estimators have no redeeming features as compared to the former two methods and have substantial disadvantages. The moment and ML estimators for parameter k appear to exhibit similar characteristics. However, the moment estimator for parameter p appears to be inferior to the ML estimators with respect to frequency and magnitude of bias. We recommend for small sample size calculating the moment estimators for p and k; the ML estimators need be calculated only if p $\geq$ k. The parameters of the negative binomial distribution were fitted by the moment and ML estimators using extensive arthropod data collected on cotton plants. In addition tests for homogeneity of k were made using Bliss and Owen's technique; the common k thus calculated was nearly always less than the average of the ML estimators.

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