zi_zipfpssFit: Zero Inflated Zipf-PSS parameters estimation.

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 zero inflated Zipf-PSS distribution by means of the maximum likelihood method. The input data should be provided as a frequency matrix.

Usage

zi_zipfpssFit(data, init_alpha = 1.5, init_lambda = 1.5,
  init_w = 0.1, level = 0.95, ...)
# S3 method for zi_zipfpssR
residuals(object, ...)
# S3 method for zi_zipfpssR
fitted(object, ...)
# S3 method for zi_zipfpssR
coef(object, ...)
# S3 method for zi_zipfpssR
plot(x, ...)
# S3 method for zi_zipfpssR
print(x, ...)
# S3 method for zi_zipfpssR
summary(object, ...)
# S3 method for zi_zipfpssR
logLik(object, ...)
# S3 method for zi_zipfpssR
AIC(object, ...)
# S3 method for zi_zipfpssR
BIC(object, ...)

Arguments

data

Matrix of count data in form of table of frequencies.

init_alpha

Initial value of \(\alpha\) parameter (\(\alpha > 1\)).

init_lambda

Initial value of \(\lambda\) parameter (\(\lambda > 0\)).

init_w

Initial value of \(w\) parameter (\(0 < w < 1\)).

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 "zpssR" (output of zipfpssFit function).

Details

The argument data is a two column matrix with the first column containing the observations and the second column containing their frequencies.

References

Panjer, H. H. (1981). Recursive evaluation of a family of compound distributions. ASTIN Bulletin: The Journal of the IAA, 12(1), 22-26.

Sundt, B., & Jewell, W. S. (1981). Further results on recursive evaluation of compound distributions. ASTIN Bulletin: The Journal of the IAA, 12(1), 27-39.

Examples

Run this code

# NOT RUN {
data <- rzipfpss(100, 2.5, 1.3)
data <- as.data.frame(table(data))
data[,1] <- as.numeric(as.character(data[,1]))
data[,2] <- as.numeric(as.character(data[,2]))
obj <- zipfpssFit(data, init_alpha = 1.5, init_lambda = 1.5)
# }