# pgfDlogarithmicpoisson: Function pgfDlogarithmicpoisson In Compounding: Computing Continuous Distributions

## Description

This function calculates value of the pgf's first derivative of the logarithmic-Poisson distribution.

## Usage

 `1` ```pgfDlogarithmicpoisson(s, params) ```

## Arguments

 `s` Value of the parameter of the pgf. It should be from interval [-1,1]. In the opposite pgf diverges. `params` List of the parameters of the logarithmic-Poisson distribution, such that params<-c(theta,lambda), where theta is the probability, lambda is the positive number.

## Author(s)

S. Nadarajah, B. V. Popovic, M. M. Ristic

## References

Johnson N, Kotz S, Kemp A (1992) Univariate Discrete Distributions, John Wiley and Sons, New York

http://www.am.qub.ac.uk/users/g.gribakin/sor/Chap3.pdf

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21``` ```params<-c(.9,7) pgfDlogarithmicpoisson(.5,params) ## The function is currently defined as pgfDlogarithmicpoisson <- function(s,params) { k<-s[abs(s)>1] if (length(k)>0) warning("At least one element of the vector s are out of interval [-1,1]") if (length(params)<2) stop("At least one value in params is missing") if (length(params)>2) stop("The length of params is 2") theta<-params[1] lambda<-params[2] if ((theta>=1)|(theta<=0)) stop ("Parameter theta belongs to the interval (0,1)") if (lambda<=0) stop ("Parameter lambda must be positive") -lambda*(1-theta)/log(theta)*exp(lambda*(s-1))/(1-(1-theta)*exp(lambda*(s-1))) } ```

Compounding documentation built on May 2, 2019, 1:04 p.m.