Discrete Weibull (Type 1) {DiscreteWeibull} R Documentation

## The type 1 discrete Weibull distribution

### Description

Probability mass function, distribution function, quantile function and random generation for the discrete Weibull distribution with parameters q and \beta

### Usage

ddweibull(x, q, beta, zero = FALSE)
pdweibull(x, q, beta, zero = FALSE)
qdweibull(p, q, beta, zero = FALSE)
rdweibull(n, q, beta, zero = FALSE)


### Arguments

 x vector of quantiles p vector of probabilities q first parameter beta second parameter zero TRUE, if the support contains 0; FALSE otherwise n sample size

### Details

The discrete Weibull distribution has probability mass function given by P(X=x;q,\beta)=q^{(x-1)^{\beta}}-q^{x^{\beta}}, x=1,2,3,\ldots, if zero=FALSE; or P(X=x;q,\beta)=q^{x^{\beta}}-q^{(x+1)^{\beta}}, x=0,1,2,\ldots, if zero=TRUE. The cumulative distribution function is F(x;q,\beta)=1-q^{x^{\beta}} if zero=FALSE; F(x;q,\beta)=1-q^{(x+1)^{\beta}} otherwise

### Value

ddweibull gives the probability function, pdweibull gives the distribution function, qdweibull gives the quantile function, and rdweibull generates random values.

### Author(s)

Alessandro Barbiero

### Examples

# Ex.1
x <- 1:10
q <- 0.6
beta <- 0.8
ddweibull(x, q, beta)
t <- qdweibull(0.99, q, beta)
t
pdweibull(t, q, beta)
#
x <- 0:10
ddweibull(x, q, beta, zero=TRUE)
t <- qdweibull(0.99, q, beta, zero=TRUE)
t
pdweibull(t, q, beta, zero=TRUE)

# Ex.2
q <- 0.4
beta <- 0.7
n <- 100
x <- rdweibull(n, q, beta)
tabulate(x)/sum(tabulate(x))
y <- 1:round(max(x))
# compare with
ddweibull(y, q, beta)


[Package DiscreteWeibull version 1.1 Index]