The Inverse Gamma Distribution.
invgamma
invgamma implements the (d/p/q/r)
statistics functions for the inverse gamma distribution in R. It is ideal for using in other packages since it is lightweight and leverages the (d/p/q/r)gamma()
line of functions maintained by CRAN.
Getting invgamma
There are two ways to get invgamma. For the CRAN version, use
install.packages("invgamma")
For the development version, use
# install.packages("devtools")
devtools::install_github("dkahle/invgamma")
The (d/p/q/r)invgamma()
functions
The functions in invgamma match those for the gamma distribution provided by the stats package. Namely, it uses as its density f(x) = (b^a / Gamma(a)) x^-(a+1) e^(-b/x), where a = shape
and b = rate
.
The PDF (the f(x) above) can be evaluated with the dinvgamma()
function:
library(invgamma)
library(ggplot2); theme_set(theme_bw())
x <- seq(0, 5, .01)
qplot(x, dinvgamma(x, 7, 10), geom = "line")
# Warning: Removed 1 rows containing missing values (geom_path).
The CDF can be evaluated with the pinvgamma()
function:
f <- function(x) dinvgamma(x, 7, 10)
q <- 2
integrate(f, 0, q)
# 0.7621835 with absolute error < 7.3e-05
(p <- pinvgamma(q, 7, 10))
# [1] 0.7621835
The quantile function can be evaluated with qinvgamma()
:
qinvgamma(p, 7, 10) # = q
# [1] 2
And random number generation can be performed with rinvgamma()
:
set.seed(1)
rinvgamma(5, 7, 10)
# [1] 1.9996157 0.9678268 0.9853343 1.3157697 3.1578177
rinvgamma()
can be used to obtain a Monte Carlo estimate of the probability given by pinvgamma()
above:
samples <- rinvgamma(1e5, 7, 10)
mean(samples <= q)
# [1] 0.7621
Moreover, we can check the consistency and correctness of the implementation with
qplot(samples, geom = "density") +
stat_function(fun = f, color = "red")
The (d/p/q/r)invchisq()
and (d/p/q/r)invexp()
functions
The gamma distribution subsumes the chi-squared and exponentialdistributions, so it makes sense to include the *invchisq()
and *invexp()
functions in invgamma. Their implementations, however, wrap *chisq()
and *exp()
, not *invgamma()
.