For a given sample of strictly positive integer numbers, usually of the type of ranking data or frequencies of frequencies data, estimates the parameters of the ZipfPolylog distribution by means of the maximum likelihood method. The input data should be provided as a frequency matrix.
zipfPolylogFit(data, init_alpha, init_beta, level = 0.95, ...)# S3 method for zipfPolyR
residuals(object, ...)
# S3 method for zipfPolyR
fitted(object, ...)
# S3 method for zipfPolyR
coef(object, ...)
# S3 method for zipfPolyR
plot(x, ...)
# S3 method for zipfPolyR
print(x, ...)
# S3 method for zipfPolyR
summary(object, ...)
# S3 method for zipfPolyR
logLik(object, ...)
# S3 method for zipfPolyR
AIC(object, ...)
# S3 method for zipfPolyR
BIC(object, ...)
Matrix of count data in form of a table of frequencies.
Initial value of \(\alpha\) parameter (\(\alpha > 1\)).
Initial value of \(\beta\) parameter (\(\beta > 0\)).
Confidence level used to calculate the confidence intervals (default 0.95).
Further arguments to the generic functions. The extra arguments are passing to the optim function.
An object from class "zipfPolyR" (output of zipfPolylogFit function).
An object from class "zipfPolyR" (output of zipfPolylogFit function).
Returns a zipfPolyR object composed by the maximum likelihood parameter estimations jointly with their standard deviation and confidence intervals. It also contains the value of the log-likelihood at the maximum likelihood estimator.
The argument data is a two column matrix with the first column containing the observations and
the second column containing their frequencies.
The log-likelihood function is equal to:
The function optim is used to estimate the parameters.