This function computes the log-likelihood function for the mixture of two negative binomial distribution as described in
negbinom.loglik(theta, N, E)
vector of parameter values.
vector of observed error profiles counts.
vector of expected error profiles counts.
For further details see Myers et al. (2011).
negbinom.loglik returns the log-likelihood value for the negative binomial distribution.
Sergio Venturini [email protected],
Jessica A. Myers [email protected]
DuMouchel W. (1999), "Bayesian Data Mining in Large Frequency Tables, with an Application to the FDA Spontaneous Reporting System". The American Statistician, 53, 177-190.
Myers, J. A., Venturini, S., Dominici, F. and Morlock, L. (2011), "Random Effects Models for Identifying the Most Harmful Medication Errors in a Large, Voluntary Reporting Database". Technical Report.
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