| SichelDistribution | R Documentation |
Density, distribution function, quantile function, and random generation for the Sichel distribution.
dsichel(x, mu = 1, sigma = 1, gamma = 1, log = FALSE)
psichel(q, mu = 1, sigma = 1, gamma = 1, lower.tail = TRUE, log.p = FALSE)
qsichel(p, mu = 1, sigma = 1, gamma = 1, lower.tail = TRUE, log.p = FALSE)
rsichel(n, mu = 1, sigma = 1, gamma = 1)
x |
numeric value or vector of non-negative integer values. |
mu |
numeric; mean of the distribution (mu > 0). |
sigma |
numeric; scale parameter (sigma > 0). |
gamma |
numeric; shape parameter (can be any real number). |
log, log.p |
logical; if TRUE, probabilities are given as log(p). |
q |
quantile or vector of quantiles. |
lower.tail |
logical; if TRUE, probabilities are P[X <= x]. |
p |
probability or vector of probabilities. |
n |
number of random values to generate. |
The Sichel distribution is a three-parameter discrete distribution that generalizes the Poisson-inverse Gaussian distribution. It is useful for modeling overdispersed count data.
The PMF is:
f(y|\mu, \sigma, \gamma) =
\frac{(\mu/c)^y K_{y+\gamma}(\alpha)}{K_\gamma(1/\sigma) y!
(\alpha\sigma)^{y+\gamma}}
dsichel gives the density, psichel gives the distribution function, qsichel gives the quantile function, and rsichel generates random deviates.
The length of the result is determined by n for rsichel, and is the maximum of the lengths of the numerical arguments for the other functions.
Rigby, R. A., Stasinopoulos, D. M., & Akantziliotou, C. (2008). A framework for modelling overdispersed count data, including the Poisson-shifted generalized inverse Gaussian distribution. Computational Statistics & Data Analysis, 53(2), 381-393.
# Basic usage
dsichel(0:10, mu = 5, sigma = 1, gamma = -0.5)
# Log-probabilities for numerical stability
dsichel(0:10, mu = 5, sigma = 1, gamma = -0.5, log = TRUE)
# CDF
psichel(5, mu = 5, sigma = 1, gamma = -0.5)
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