These functions provide density, distribution function, quantile function, and random number generation for the Poisson-Weibull Distribution, which is specified either by its shape and scale parameters or by its mean and standard deviation.
dpoisweibull(
x,
lambda = NULL,
alpha = NULL,
sigma = NULL,
mean_value = NULL,
sd_value = NULL,
ndraws = 1500,
log = FALSE
)ppoisweibull(
q,
lambda = NULL,
alpha = NULL,
sigma = NULL,
mean_value = NULL,
sd_value = NULL,
ndraws = 1500,
lower.tail = TRUE,
log.p = FALSE
)
qpoisweibull(
p,
lambda = NULL,
alpha = NULL,
sigma = NULL,
mean_value = NULL,
sd_value = NULL,
ndraws = 1500
)
rpoisweibull(
n,
lambda = NULL,
alpha = NULL,
sigma = NULL,
mean_value = NULL,
sd_value = NULL,
ndraws = 1500
)
dpoisweibull gives the density, ppoisweibull gives the distribution function, qpoisweibull gives the quantile function, and rpoisweibull generates random deviates.
The length of the result is determined by n for rpoisweibull, and is the maximum of the lengths of the numerical arguments for the other functions.
A numeric value or vector of values for which the PDF or CDF is calculated.
Mean value of the Poisson distribution.
Shape parameter of the Weibull distribution (optional if mean and sd are provided).
Scale parameter of the Weibull distribution (optional if mean and sd are provided).
Mean of the Weibull distribution (optional if alpha and sigma are provided).
Standard deviation of the Weibull distribution (optional if alpha and sigma are provided).
the number of Halton draws to use for the integration.
Logical; if TRUE, probabilities p are given as log(p).
Quantile or a vector of quantiles.
Logical; if TRUE, probabilities are P[X <= x], otherwise P[X > x].
Logical; if TRUE, probabilities p are given as log(p).
A numeric value or vector of probabilities for the quantile function.
The number of random samples to generate.
The Poisson-Weibull distribution uses the Weibull distribution as a mixing distribution for a Poisson process. It is useful for modeling overdispersed count data. The density function (probability mass function) for the Poisson-Weibull distribution is given by: $$P(y|\lambda,\alpha,\sigma) = \int_0^\infty \frac{e^{-\lambda x} \lambda^y x^y }{y!} \left(\frac{\alpha}{\sigma}\right) \left(\frac{x}{\sigma}\right)^{\alpha-1} e^{-\left(\frac{x}{\sigma}\right)^\alpha} dx$$ where \(f(x| \alpha, \sigma)\) is the PDF of the Weibull distribution and \(\lambda\) is the mean of the Poisson distribution.
dpoisweibull computes the density of the Poisson-Weibull distribution.
ppoisweibull computes the distribution function of the Poisson-Weibull
distribution.
qpoisweibull computes the quantile function of the Poisson-Weibull
distribution.
rpoisweibull generates random numbers following the Poisson-Weibull
distribution.
The shape and scale parameters directly define the Weibull distribution, whereas the mean and standard deviation are used to compute these parameters indirectly.
dpoisweibull(4, lambda=1.5, mean_value=1.5, sd_value=0.5, ndraws=10)
ppoisweibull(4, lambda=1.5, mean_value=1.5, sd_value=2, ndraws=10)
qpoisweibull(0.95, lambda=1.5, mean_value=1.5, sd_value=2, ndraws=10)
rpoisweibull(10, lambda=1.5, mean_value=1.5, sd_value=2, ndraws=10)
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