| ANOLLG {ollg} | R Documentation |
A New Odd log-logistic family of distributions (ANOLL-G)
Description
Computes the pdf, cdf, hdf, quantile and random numbers of the beta extended distribution due to Haghbin et al. (2017) specified by the pdf
f=\frac{\alpha\beta\,g\,\bar{G}^{\alpha\beta-1}[1-\bar{G}^\alpha]^{\beta-1}}{\{[1-\bar{G}^\alpha]^\beta+\bar{G}^{\alpha\beta}\}^2}
for G any valid continuous cdf , \bar{G}=1-G, g the corresponding pdf, \alpha > 0, the first shape parameter, and \beta > 0, the second shape parameter.
Usage
panollg(x, alpha = 1, beta = 1, G = pnorm, ...)
danollg(x, alpha = 1, beta = 1, G = pnorm, ...)
qanollg(q, alpha = 1, beta = 1, G = pnorm, ...)
ranollg(n, alpha = 1, beta = 1, G = pnorm, ...)
hanollg(x, alpha = 1, beta = 1, G = pnorm, ...)
Arguments
x |
scaler or vector of values at which the pdf or cdf needs to be computed. |
alpha |
the value of the first shape parameter, must be positive, the default is 1. |
beta |
the value of the second shape parameter, must be positive, the default is 1. |
G |
A baseline continuous cdf. |
... |
The baseline cdf parameters. |
q |
scaler or vector of probabilities at which the quantile needs to be computed. |
n |
number of random numbers to be generated. |
Value
panollg gives the distribution function,
danollg gives the density,
qanollg gives the quantile function,
hanollg gives the hazard function and
ranollg generates random variables from the A New Odd log-logistic family of
distributions (ANOLL-G) for baseline cdf G.
References
Haghbin, Hossein, et al. "A new generalized odd log-logistic family of distributions." Communications in Statistics-Theory and Methods 46.20(2017): 9897-9920.
Examples
x <- seq(0, 1, length.out = 21)
panollg(x)
panollg(x, alpha = 2, beta = 2, G = pbeta, shape1 = 1, shape2 = 2)
danollg(x, alpha = 2, beta = 2, G = pbeta, shape1 = 1, shape2 = 2)
curve(danollg, -3, 3)
qanollg(x, alpha = 2, beta = 2, G = pbeta, shape1 = 1, shape2 = 2)
n <- 10
ranollg(n, alpha = 2, beta = 2, G = pbeta, shape1 = 1, shape2 = 2)
hanollg(x, alpha = 2, beta = 2, G = pbeta, shape1 = 1, shape2 = 2)
curve(hanollg, -3, 3)