Negative binomial distribution maximum likelihood estimation

For the density function of the Negative binomial distribution see Negative binomial.

Usage

mlnbinom(x, na.rm = FALSE, ...)

Arguments

x: a (non-empty) numeric vector of data values.
na.rm: logical. Should missing values be removed?
...: The arguments size can be specified to only return the ml of prob. reltol is the relative accuracy requested, defaults to .Machine$double.eps^0.25. iterlim is a positive integer specifying the maximum number of iterations to be performed before the program is terminated (defaults to 100).

Value

mlnbinom returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for size and prob and the following attributes:

model: The name of the model.
density: The density associated with the estimates.
logLik: The loglikelihood at the maximum.
support: The support of the density.
n: The number of observations.
call: The call as captured my match.call

References

Johnson, N. L., Kemp, A. W., & Kotz, S. (2005). Univariate Discrete Distributions (3rd ed.). Wiley-Blackwell.

Examples

mlnbinom(corbet)
#> Maximum likelihood estimates for the Negative binomial model 
#>  size   prob  
#> 1.390  0.174