zipfPolylogFit: ZipfPolylog parameters estimation.

In zipfextR: Zipf Extended Distributions

Description

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.

Usage

zipfPolylogFit(data, init_alpha, init_beta, level = 0.95, ...)

## S3 method for class 'zipfPolyR'
residuals(object, ...)

## S3 method for class 'zipfPolyR'
fitted(object, ...)

## S3 method for class 'zipfPolyR'
coef(object, ...)

## S3 method for class 'zipfPolyR'
plot(x, ...)

## S3 method for class 'zipfPolyR'
print(x, ...)

## S3 method for class 'zipfPolyR'
summary(object, ...)

## S3 method for class 'zipfPolyR'
logLik(object, ...)

## S3 method for class 'zipfPolyR'
AIC(object, ...)

## S3 method for class 'zipfPolyR'
BIC(object, ...)

Arguments

data	Matrix of count data in form of a table of frequencies.
init_alpha	Initial value of α parameter (α > 1).
init_beta	Initial value of β parameter (β > 0).
level	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.
object	An object from class "zipfPolyR" (output of zipfPolylogFit function).
x	An object from class "zipfPolyR" (output of zipfPolylogFit function).

Details

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.

Value

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.

zipfextR documentation built on July 8, 2020, 6:23 p.m.