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VGAM (version 0.7-1)

dagum: Dagum Distribution Family Function

Description

Maximum likelihood estimation of the 3-parameter Dagum distribution.

Usage

dagum(link.a = "loge", link.scale = "loge", link.p = "loge",
      init.a = NULL, init.scale = NULL, init.p = 1, zero = NULL)

Arguments

Value

  • An object of class "vglmff" (see vglmff-class). The object is used by modelling functions such as vglm, and vgam.

Details

The 3-parameter Dagum distribution is the 4-parameter generalized beta II distribution with shape parameter $q=1$. It is known under various other names, such as the Burr III, inverse Burr, beta-K, and 3-parameter kappa distribution. It can be considered a generalized log-logistic distribution. Some distributions which are special cases of the 3-parameter Dagum are the inverse Lomax ($a=1$), Fisk ($p=1$), and the inverse paralogistic ($a=p$). More details can be found in Kleiber and Kotz (2003).

The Dagum distribution has a cumulative distribution function $$F(y) = [1 + (y/b)^{-a}]^{-p}$$ which leads to a probability density function $$f(y) = ap y^{ap-1} / [b^{ap} {1 + (y/b)^a}^{p+1}]$$ for $a > 0$, $b > 0$, $p > 0$, $y > 0$. Here, $b$ is the scale parameter scale, and the others are shape parameters. The mean is $$E(Y) = b \, \Gamma(p + 1/a) \, \Gamma(1 - 1/a) / \Gamma(p)$$ provided $-ap < 1 < a$.

References

Kleiber, C. and Kotz, S. (2003) Statistical Size Distributions in Economics and Actuarial Sciences, Hoboken, NJ: Wiley-Interscience.

See Also

Dagum, genbetaII, betaII, sinmad, fisk, invlomax, lomax, paralogistic, invparalogistic.

Examples

Run this code
y = rdagum(n=3000, 4, 6, 2)
fit = vglm(y ~ 1, dagum, trace=TRUE)
fit = vglm(y ~ 1, dagum(init.a=2.1), trace=TRUE, crit="c")
coef(fit, mat=TRUE)
Coef(fit)
summary(fit)

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