dgBeta: Generalized Beta Distribution.

In sgr: Sample Generation by Replacement

Generalized Beta Distribution.

Description

The generalized beta distribution extends the classical beta distribution beyond the [0,1] range (Whitby, 1971).

Usage

dgBeta(x, a = min(x), b = max(x), gam = 1, del = 1)

Arguments

x	Vector of quantilies.
a	Minimum of range of r.v. X.
b	Maximum of range of r.v. X.
gam	Gamma parameter.
del	Delta parameter.

Details

The Generalized Beta Distribution is defined as follows:

G(x;a,b,γ,δ) = \frac{1}{B(γ,δ)(b-a)^{γ+δ-1}} (x-a)^{γ-1}(b-x)^{δ-1}

where B(γ,δ) is the beta function. The parameters a \in R and b \in R (with a < b) are the left and right end points, respectively. The parameters γ > 0 and δ > 0 are the governing shape parameters for a and b respectively. For all the values of the r.v. X that fall outside the interval [a, b], G simply takes value 0. The generalized beta distribution reduces to the beta distribution when a = 0 and b = 1.

Value

Gives the density.

Author(s)

Massimiliano Pastore & Luigi Lombardi

References

Whitby, O. (1971). Estimation of parameters in the generalized beta distribution (Technical Report NO. 29). Department of Statistics: Standford University.

See Also

dgBetaD

Examples

curve(dgBeta(x))
curve(dgBeta(x,gam=3,del=3))
curve(dgBeta(x,gam=1.5,del=2.5))

x <- 1:7
GA <- c(1,3,1.5,8); DE <- c(1,3,4,2.5)
par(mfrow=c(2,2))
for (j in 1:4) {
  plot(x,dgBeta(x,gam=GA[j],del=DE[j]),type="h",
       panel.first=points(x,dgBeta(x,gam=GA[j],del=DE[j]),pch=19),
       main=paste("gamma=",GA[j]," delta=",DE[j],sep=""),ylim=c(0,.6),
       ylab="dgBeta(x)")  
}

sgr documentation built on April 14, 2022, 5:08 p.m.