Adjustment for Maximum Likelihood Estimate of Negative Binomial Dispersion Parameter
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چکیده
منابع مشابه
Adjustment for the Maximum Likelihood Estimate of the Negative Binomial Dispersion Parameter
Negative Binomial (or Poisson-gamma) model has been used extensively by highway safety analysts because it can accommodate the over-dispersion, often exhibited in crash data. However, it has been reported in the literature that the maximum likelihood estimate of the dispersion parameter of NB models can be significantly affected when the data are characterized by small sample size and low sampl...
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BACKGROUND The negative binomial distribution is used commonly throughout biology as a model for overdispersed count data, with attention focused on the negative binomial dispersion parameter, k. A substantial literature exists on the estimation of k, but most attention has focused on datasets that are not highly overdispersed (i.e., those with k>or=1), and the accuracy of confidence intervals ...
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The objective of this study is to improve the estimation of the dispersion parameter of the negative binomial distribution for modeling motor vehicle collisions. The negative binomial distribution is widely used to model count data such as traffic crash data, which often exhibit low sample mean values and small sample sizes. Under such situations, the most commonly used methods for estimating t...
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The problem of estimating the parameters for continuous-time partially observed systems is discussed. New exact lters for obtaining Maximum Likelihood (ML) parameter estimates via the Expectation Maximization algorithm are derived. The methodology exploits relations between incomplete and complete data likelihood and gradient of likelihood functions, which are derived using Girsanov's measure t...
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ژورنال
عنوان ژورنال: Transportation Research Record: Journal of the Transportation Research Board
سال: 2008
ISSN: 0361-1981,2169-4052
DOI: 10.3141/2061-02