dist.Inverse.ChiSquare {LaplacesDemon} | R Documentation |
(Scaled) Inverse Chi-Squared Distribution
Description
This is the density function and random generation for the (scaled) inverse chi-squared distribution.
Usage
dinvchisq(x, df, scale, log=FALSE)
rinvchisq(n, df, scale=1/df)
Arguments
x |
This is a vector of quantiles. |
n |
This is the number of observations. If |
df |
This is the degrees of freedom parameter, usually
represented as |
scale |
This is the scale parameter, usually represented as
|
log |
Logical. If |
Details
Application: Continuous Univariate
Density:
p(\theta) = \frac{{\nu/2}^{\nu/2}}{\Gamma(\nu/2)} \lambda^\nu \frac{1}{\theta}^{\nu/2+1} \exp(-\frac{\nu \lambda^2}{2\theta}), \theta \ge 0
Inventor: Derived from the chi-squared distribution
Notation 1:
\theta \sim \chi^{-2}(\nu, \lambda)
Notation 2:
p(\theta) = \chi^{-2}(\theta | \nu, \lambda)
Parameter 1: degrees of freedom parameter
\nu > 0
Parameter 2: scale parameter
\lambda
Mean:
E(\theta)
= unknownVariance:
var(\theta)
= unknownMode:
mode(\theta) =
The inverse chi-squared distribution, also called the
inverted chi-square distribution, is the multiplicate inverse of the
chi-squared distribution. If x
has the chi-squared distribution
with \nu
degrees of freedom, then 1 / x
has the
inverse chi-squared distribution with \nu
degrees of freedom,
and \nu / x
has the inverse chi-squared distribution with
\nu
degrees of freedom.
These functions are similar to those in the GeoR package.
Value
dinvchisq
gives the density and
rinvchisq
generates random deviates.
See Also
Examples
library(LaplacesDemon)
x <- dinvchisq(1,1,1)
x <- rinvchisq(10,1)
#Plot Probability Functions
x <- seq(from=0.1, to=5, by=0.01)
plot(x, dinvchisq(x,0.5,1), ylim=c(0,1), type="l", main="Probability Function",
ylab="density", col="red")
lines(x, dinvchisq(x,1,1), type="l", col="green")
lines(x, dinvchisq(x,5,1), type="l", col="blue")
legend(3, 0.9, expression(paste(nu==0.5, ", ", lambda==1),
paste(nu==1, ", ", lambda==1), paste(nu==5, ", ", lambda==1)),
lty=c(1,1,1), col=c("red","green","blue"))