# poistweedie: Poisson-Tweedie (Some discrete exponential dispersion models) In poistweedie: Poisson-Tweedie exponential family models

## Description

Density, Log of density, variance for the Poisson-Tweedie family of distributions

## Usage

 ```1 2 3 4 5 6``` ```poistweedie(x, n, p, mu, lambda, theta0, lower.tail = TRUE, log.p = FALSE, fonction = "PROBABILITE") poisson(x, n, p, lambda1, lower.tail = TRUE, log.p = FALSE, fonction = "PROBABILITE") nbinomiale(x, n, p, lambda1, p1, lower.tail = TRUE, log.p = FALSE, fonction = "PROBABILITE") ```

## Arguments

 `x` vector of (non-negative integer) quantiles. `p` is a real index related to a precise model. `p1` is a real index related to a precise model. `n` non-negative integer `mu` the mean. `lambda` the dispersion parameter. `lambda1` the dispersion parameter. `theta0` the canonical parameter. `log, log.p` logical; if TRUE, probabilities p are given as log(p). `lower.tail` logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]. `fonction` is a string

## Details

Density, Log of density, variance for the Poisson-Tweedie family of distributions

## Author(s)

Cactha David Pechel, Laure Pauline Fotso and Celestin C Kokonendji Maintainer: Cactha David Pechel ( <[email protected]>)

`dpoistweedie`, `ppoistweedie`
 ```1 2 3 4 5 6 7 8 9``` ```## poistweedie(x, n, p, mu, lambda, theta0, lower.tail = TRUE, ## log.p = FALSE, fonction = "PROBABILITE") x <- 0:200 p <- 1.5 mu <-10 lambda <- 10 theta0<--10 d1<-poistweedie(x, n, p, mu, lambda, theta0, lower.tail = TRUE, log.p = FALSE, fonction = "PROBABILITE") ```