Zipf distribution maximum likelihood estimation

For the density function of the Zipf distribution see Zipf.

Usage

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

Arguments

x: a (non-empty) numeric vector of data values.
na.rm: logical. Should missing values be removed?
...: Not currently in use.

Value

mlzipf returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for N and s 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

Details

This function follows the same format as every other function in the package, but most applications of Zipf's law use rank-abundance data. See, e.g., sads::fitzipf for estimation of this sort of data.

References

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

Examples

AIC(mlzipf(corbet)) # 2729.536
#> [1] 2729.536
AIC(mllgser(corbet)) # 2835.883
#> [1] 2835.883