Lomax | R Documentation |
Density function, distribution function, quantile function and random generation for the Lomax distribution.
dlomax(x, scale = 1.0, shape = 4.0, log = FALSE)
plomax(q, scale = 1.0, shape = 4.0, lower.tail = TRUE)
qlomax(p, scale = 1.0, shape = 4.0)
rlomax(n, scale = 1.0, shape = 4.0)
x, q |
Vector of quantiles. |
p |
Vector of probabilities. |
n |
Number of observations. |
scale, shape |
Scale and shape parameters. Vectors of length > 1 are not accepted. |
log |
Logical; if |
lower.tail |
Logical; if |
The Lomax distribution function with shape \alpha > 0
and scale
\beta > 0
has survival function
S(y) = \left[1 + y/\beta \right]^{-\alpha} \qquad (y > 0)
This distribution has increasing hazard and decreasing mean
residual life (MRL). The coefficient of variation decreases with
\alpha
, and tends to 1
for large \alpha
. The
default value \alpha=4
corresponds to \textrm{CV} =
\sqrt{2}
.
dlomax
gives the density function, plomax
gives the
distribution function, qlomax
gives the quantile function, and
rlomax
generates random deviates.
This distribution is sometimes called log-exponential. It is a
special case of Generalised Pareto Distribution (GPD) with positive
shape \xi > 0
, scale \sigma
and location \mu=0
. The
Lomax and GPD parameters are related according to
\alpha =
1/\xi, \qquad \beta = \sigma/\xi.
The Lomax distribution can be used in POT to describe
excesses following GPD with shape \xi>0
thus with decreasing
hazard and increasing Mean Residual Life.
Note that the exponential distribution with rate \nu
is the
limit of a Lomax distribution having large scale \beta
and large
shape \alpha
, with the constraint on the shape/scale ratio
\alpha/\beta = \nu
.
Johnson N. Kotz S. and N. Balakrishnan Continuous Univariate Distributions vol. 1, Wiley 1994.
Lomax distribution in Wikipedia
flomax
to fit the Lomax distribution by Maximum
Likelihood.
shape <- 5; scale <- 10
xl <- qlomax(c(0.00, 0.99), scale = scale, shape = shape)
x <- seq(from = xl[1], to = xl[2], length.out = 200)
f <- dlomax(x, scale = scale, shape = shape)
plot(x, f, type = "l", main = "Lomax density")
F <- plomax(x, scale = scale, shape = shape)
plot(x, F, type ="l", main ="Lomax distribution function")
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