Description Usage Arguments Details Value Author(s) Source References See Also Examples
Probability mass function, distribution function, quantile function and random number generation for the one-parameter discrete Lindley distribution with parameter theta.
1 2 3 4 5 6 7 |
x, q |
vector of integer positive quantiles. |
theta |
positive parameter. |
log, log.p |
logical; If TRUE, probabilities p are given as log(p). |
lower.tail |
logical; If TRUE, (default), P(X ≤q x) are returned, otherwise P(X > x). |
p |
vector of probabilities. |
n |
number of observations. If |
Probability mass function
P≤ft( X=x\mid θ \right) =∑\limits_{i=0}^{1}≤ft( -1\right) ^{i}≤ft( 1+\frac{θ }{1+θ }≤ft( x+i\right) \right) e^{-θ ≤ft( x+i\right) }
ddlindley
gives the probability mass function, pdlindley
gives the distribution function, qdlindley
gives the quantile function and rdlindley
generates random deviates.
Invalid arguments will return an error message.
Josmar Mazucheli jmazucheli@gmail.com
Larissa B. Fernandes lbf.estatistica@gmail.com
[d-p-q-r]dlindley are calculated directly from the definitions. rdlindley
uses the discretize values.
Bakouch, H. S., Jazi, M. A. and Nadarajah, S. (2014). A new discrete distribution. Statistics: A Journal of Theoretical and Applied Statistics, 48, 1, 200-240.
Gomez-Deniz, E. and Calderín-Ojeda, E. (2013). The discrete Lindley distribution: properties and applications. Journal of Statistical Computation and Simulation, 81, 11, 1405-1416.
1 2 3 4 5 6 7 8 9 10 11 | set.seed(1)
x <- rdlindley(n = 1000, theta = 1.5)
plot(table(x) / sum(table(x)))
points(unique(x),ddlindley(unique(x), theta = 1.5))
## fires in Greece data (from Bakouch et al., 2014)
data(fires)
library(fitdistrplus)
fit <- fitdist(fires, 'dlindley', start = list(theta = 0.30), discrete = TRUE)
gofstat(fit, discrete = TRUE)
plot(fit)
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