igamma {pscl} | R Documentation

## inverse-Gamma distribution

### Description

Density, distribution function, quantile function, and highest density region calculation for the inverse-Gamma distribution with parameters `alpha` and `beta`.

### Usage

    	densigamma(x,alpha,beta)
      	pigamma(q,alpha,beta)
    	qigamma(p,alpha,beta)
    	rigamma(n,alpha,beta)
    	igammaHDR(alpha,beta,content=.95,debug=FALSE)

### Arguments

`x,q` | vector of quantiles
`p` | vector of probabilities
`n` | number of random samples in `rigamma`
`alpha,beta` | rate and shape parameters of the inverse-Gamma density, both positive
`content` | scalar, 0 < `content` < 1, volume of highest density region
`debug` | logical; if TRUE, debugging information from the search for the HDR is printed

### Details

The inverse-Gamma density arises frequently in Bayesian analysis of normal data, as the (marginal) conjugate prior for the unknown variance parameter. The inverse-Gamma density for x>0 with parameters α>0 and β>0 is

(beta^alpha)/Gamma(alpha) x^(-alpha-1) exp(-beta/x)

where Γ(x) is the `gamma` function

Gamma(a) = int_0^infty t^(a-1) exp(-t) dt

and so ensures f(x) integrates to one. The inverse-Gamma density has a mean at beta/(alpha-1) for alpha>1 and has variance beta^2/((alpha-1)^2 (alpha-2)) for alpha>2. The inverse-Gamma density has a unique mode at beta/(alpha+1).

The evaluation of the density, cumulative distribution function and quantiles is done by calls to the `dgamma`, `pgamma` and `igamma` functions, with the arguments appropriately transformed. That is, note that if x ~ IG(alpha,beta then 1/x ~ G(alpha,beta).

Highest Density Regions. In general, suppose x has a density f(x), where x \in Θ. Then a highest density region (HDR) for x with content p \in (0,1] is a region (or set of regions) \mathcal{Q} \subseteq Θ such that:

int_Q f(x) dx = p

and

f(x) > f(x*) for all x in Q and all x* not in Q.

For a continuous, unimodal density defined with respect to a single parameter (like the inverse-Gamma case considered here with parameters 0 < α < ∞, \,\, 0 < β < ∞), a HDR region Q of content p (with 0 < p < 1) is a unique, closed interval on the real half-line.

This function uses numerical methods to solve for the boundaries of a HDR with `content` p for the inverse-Gamma density, via repeated calls the functions `densigamma`, `pigamma` and `qigamma`. In particular, the function `uniroot` is used to find points v and w such that

f(v) = f(w)

subject to the constraint

int_v^w f(x; alpha, beta) d theta = p.

### Value

`densigamma` gives the density, `pigamma` the distribution function, `qigamma` the quantile function, `rigamma` generates random samples, and `igammaHDR` gives the lower and upper limits of the HDR, as defined above (`NA`s if the optimization is not successful).

### Note

The `densigamma` is named so as not to conflict with the `digamma` function in the R `base` package (the derivative of the `gamma` function).

### Author(s)

Simon Jackman simon.jackman@sydney.edu.au

### See Also

`gamma`, `dgamma`, `pgamma`, `qgamma`, `uniroot`

### Examples

    alpha <- 4
    beta <- 30
    summary(rigamma(n=1000,alpha,beta))

    xseq <- seq(.1,30,by=.1)
    fx <- densigamma(xseq,alpha,beta)
    plot(xseq,fx,type="n",
         xlab="x",
         ylab="f(x)",
         ylim=c(0,1.01*max(fx)),
         yaxs="i",
         axes=FALSE)
    axis(1)
    title(substitute(list(alpha==a,beta==b),list(a=alpha,b=beta)))
    q <- igammaHDR(alpha,beta,debug=TRUE)
    xlo <- which.min(abs(q[1]-xseq))
    xup <- which.min(abs(q[2]-xseq))
    plotZero <- par()$usr[3]
    polygon(x=xseq[c(xlo,xlo:xup,xup:xlo)],
            y=c(plotZero,
              fx[xlo:xup],
              rep(plotZero,length(xlo:xup))),
            border=FALSE,
            col=gray(.45))
    lines(xseq,fx,lwd=1.25)

    ## Not run:
    alpha <- beta <- .1
    xseq <- exp(seq(-7,30,length=1001))
    fx <- densigamma(xseq,alpha,beta)
    plot(xseq,fx,
         log="xy",
         type="l",
         ylim=c(min(fx),1.01*max(fx)),
         yaxs="i",
         xlab="x, log scale",
         ylab="f(x), log scale",
         axes=FALSE)
    axis(1)

    title(substitute(list(alpha==a,beta==b),list(a=alpha,b=beta)))
    q <- igammaHDR(alpha,beta,debug=TRUE)
    xlo <- which.min(abs(q[1]-xseq))
    xup <- which.min(abs(q[2]-xseq))
    plotZero <- min(fx)
    polygon(x=xseq[c(xlo,xlo:xup,xup:xlo)],
            y=c(plotZero,
              fx[xlo:xup],
              rep(plotZero,length(xlo:xup))),
            border=FALSE,
            col=gray(.45))
    lines(xseq,fx,lwd=1.25)

    ## End(Not run)

[Package pscl version 1.5.2 Index]