InvChisquare | R Documentation |
Density and random generation for the scaled inverse chi-squared
(\chi^2_{ScI}
) distribution with
df
degrees of freedom and optional non-centrality parameter
scale
.
dinvchisq(x, df, scale, log = FALSE)
rinvchisq(n, df, scale = 1/df)
x |
vector of quantiles. |
n |
number of observations. If |
df |
degrees of freedom. |
scale |
scale parameter. |
log |
logical; if TRUE, densities d are given as log(d). |
The inverse chi-squared distribution with df
= n
degrees of freedom has density
f(x) = \frac{1}{{2}^{n/2} \Gamma (n/2)} {(1/x)}^{n/2+1} {e}^{-1/(2x)}
for x > 0
.
The mean and variance are \frac{1}{(n-2)}
and
\frac{2}{(n-4)(n-2)^2}
.
The non-central chi-squared distribution with df
= n
degrees of freedom and non-centrality parameter scale
= S^2
has density
f(x) = \frac{{n/2}^{n/2}}{\Gamma (n/2)} S^n {(1/x)}^{n/2+1}
{e}^{-(n S^2)/(2x)}
,
for x \ge 0
.
The first is a particular case of the latter for \lambda = n/2
.
dinvchisq
gives the density and rinvchisq
generates random deviates.
rchisq
for the chi-squared distribution which
is the basis for this function.
set.seed(1234); rinvchisq(5, df=2)
set.seed(1234); 1/rchisq(5, df=2)
set.seed(1234); rinvchisq(5, df=2, scale=5)
set.seed(1234); 5*2/rchisq(5, df=2)
## inverse Chi-squared is a particular case
x <- 1:10
all.equal(dinvchisq(x, df=2), dinvchisq(x, df=2, scale=1/2))
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