Description Usage Arguments Value
Maximum Likelihood Estimate for the parameters of a negative binomial distribution generating a specified vector of counts. The MLE for the negative binomial should not be used with a small number of datapoints, it is known to be biased. Internally, this function is using Brent's method to find the optimal dispersion parameter.
1 2 |
counts |
a vector of counts. If a list is given, then it is assumed
to be the result of the function |
posteriors |
a vector specifying a weight for each count. The maximized function is: ∑_{i=1}{L}{posteriors[i]\log(Prob\{counts[i]\}}. If not specified, equal weights will be assumed |
old_r |
an initial value for the size parameter of the negative binomial. If not specified the methods of moments will be used for an initial guess. |
tol |
numerical tolerance of the fitting algorithm |
nthreads |
number of threads. Too many threads might worsen the performance |
A list with the parameters of the negative binomial.
mu |
the mu parameter |
r |
the size parameter |
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