lloii | R Documentation |
Density, distribution function, quantile function, and random
generation for the log-type II logistic distribution with parameters mu
and
sigma
.
dlloii(x, mu, sigma, log = FALSE, ...)
plloii(q, mu, sigma, lower.tail = TRUE, ...)
qlloii(p, mu, sigma, lower.tail = TRUE, ...)
rlloii(n, mu, sigma)
x, q |
vector of positive quantiles. |
mu |
vector of strictly positive scale parameters. |
sigma |
vector of strictly positive relative dispersion parameters. |
log |
logical; if |
... |
further arguments. |
lower.tail |
logical; if |
p |
vector of probabilities. |
n |
number of random values to return. |
A random variable X has a log-type II logistic distribution with parameter mu
and
sigma
if log(X) follows a type II logistic distribution with location parameter log(mu)
and dispersion parameter sigma
. It can be showed that mu
is the median of X.
dlloii
returns the density, plloii
gives the distribution
function, qlloii
gives the quantile function, and rlloii
generates random observations.
Invalid arguments will result in return value NaN
.
The length of the result is determined by n
for rlloii
, and is the
maximum of the lengths of the numerical arguments for the other functions.
Rodrigo M. R. de Medeiros <rodrigo.matheus@live.com>
Vanegas, L. H., and Paula, G. A. (2016). Log-symmetric distributions: statistical properties and parameter estimation. Brazilian Journal of Probability and Statistics, 30, 196-220.
mu <- 5
sigma <- 1
# Sample generation
x <- rlloii(1000, mu, sigma)
# Density
hist(x, prob = TRUE, main = "The Log-Type II Logistic Distribution", col = "white")
curve(dlloii(x, mu, sigma), add = TRUE, col = 2, lwd = 2)
legend("topright", "Probability density function", col = 2, lwd = 2, lty = 1)
# Distribution function
plot(ecdf(x), main = "The Log-Type II Logistic Distribution", ylab = "Distribution function")
curve(plloii(x, mu, sigma), add = TRUE, col = 2, lwd = 2)
legend("bottomright", c("Emp. distribution function", "Theo. distribution function"),
col = c(1, 2), lwd = 2, lty = c(1, 1)
)
# Quantile function
plot(seq(0.01, 0.99, 0.001), quantile(x, seq(0.01, 0.99, 0.001)),
type = "l",
xlab = "p", ylab = "Quantile function", main = "The Log-Type II Logistic Distribution"
)
curve(qlloii(x, mu, sigma), add = TRUE, col = 2, lwd = 2, from = 0, to = 1)
legend("topleft", c("Emp. quantile function", "Theo. quantile function"),
col = c(1, 2), lwd = 2, lty = c(1, 1)
)
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