Inverse Lomax Distribution Family Function
Maximum likelihood estimation of the 2-parameter inverse Lomax distribution.
inv.lomax(lscale = "loglink", lshape2.p = "loglink", iscale = NULL, ishape2.p = NULL, imethod = 1, gscale = exp(-5:5), gshape2.p = exp(-5:5), probs.y = c(0.25, 0.5, 0.75), zero = "shape2.p")
lscale, lshape2.p |
Parameter link functions applied to the
(positive) parameters b, and p.
See |
iscale, ishape2.p, imethod, zero |
See |
gscale, gshape2.p |
See |
probs.y |
See |
The 2-parameter inverse Lomax distribution is the 4-parameter generalized beta II distribution with shape parameters a=q=1. It is also the 3-parameter Dagum distribution with shape parameter a=1, as well as the beta distribution of the second kind with q=1. More details can be found in Kleiber and Kotz (2003).
The inverse Lomax distribution has density
f(y) = p y^(p-1) / [b^p (1 + y/b)^(p+1)]
for b > 0, p > 0, y >= 0.
Here, b is the scale parameter scale
,
and p
is a shape parameter.
The mean does not seem to exist; the median is returned
as the fitted values.
This family function handles multiple responses.
An object of class "vglmff"
(see vglmff-class
).
The object is used by modelling functions such as vglm
,
and vgam
.
See the notes in genbetaII
.
T. W. Yee
Kleiber, C. and Kotz, S. (2003). Statistical Size Distributions in Economics and Actuarial Sciences, Hoboken, NJ, USA: Wiley-Interscience.
idata <- data.frame(y = rinv.lomax(n = 2000, scale = exp(2), exp(1))) fit <- vglm(y ~ 1, inv.lomax, data = idata, trace = TRUE) fit <- vglm(y ~ 1, inv.lomax(iscale = exp(3)), data = idata, trace = TRUE, epsilon = 1e-8, crit = "coef") coef(fit, matrix = TRUE) Coef(fit) summary(fit)
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