| Loglog | R Documentation |
Density, distribution function, quantile function and random
generation for the Loglog
distribution with shape parameter alpha and scale parameter lambda.
dloglog(x, alpha, lambda, log = FALSE)
ploglog(q, alpha, lambda, lower.tail = TRUE, log.p = FALSE)
qloglog(p, alpha, lambda, lower.tail = TRUE, log.p = FALSE)
rloglog(n, alpha, lambda)
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations. If |
alpha |
shape parameter. |
lambda |
scale parameter. |
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are
|
The loglog(Pham) distribution has density
f(x) = \alpha \ln \left(\lambda\right) x^{\alpha - 1} \lambda^{x^\alpha} \exp\left\{{1 - \lambda ^{x^\alpha}}\right\};\; x > 0, \lambda > 0, \alpha > 0
where \alpha and \lambda are the shape and scale
parameters, respectively. (Pham, 2002)
dloglog gives the density,
ploglog gives the distribution function,
qloglog gives the quantile function, and
rloglog generates random deviates.
Pham, H.(2002). A Vtub-Shaped Hazard Rate Function with Applications to System Safety, International Journal of Reliability and Applications. ,Vol. 3, No. l, pp. 1-16.
Pham, H.(2006). System Software Reliability, Springer-Verlag.
.Random.seed about random number; sloglog for Loglog survival / hazard etc. functions;
data(sys2)
## Maximum Likelihood(ML) Estimates of alpha & lambda for the data(sys2)
## alpha.est = 0.9058689 lambda.est = 1.0028228
dloglog(sys2, 0.9058689, 1.0028228, log = FALSE)
ploglog(sys2, 0.9058689, 1.0028228, lower.tail = TRUE, log.p = FALSE)
qloglog(0.25, 0.9058689, 1.0028228, lower.tail=TRUE, log.p = FALSE)
rloglog(30, 0.9058689, 1.0028228)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.