mlzipf {univariateML} | R Documentation |
Zipf distribution maximum likelihood estimation
Description
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. |
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.
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 |
References
Johnson, N. L., Kemp, A. W., & Kotz, S. (2005). Univariate Discrete Distributions (3rd ed.). Wiley-Blackwell.
See Also
Zipf for the density.
Examples
AIC(mlzipf(corbet)) # 2729.536
AIC(mllgser(corbet)) # 2835.883