R: Inverse Gamma Distribution in Prior Sample Size...
rinvgamma2
R Documentation
Inverse Gamma Distribution in Prior Sample Size Parameterization
Description
Random draws and density of inverse gamma distribution parametrized
in prior sample size n0 and prior variance var0
(see Gelman et al., 2014).
Usage
rinvgamma2(n, n0, var0)
dinvgamma2(x, n0, var0)
Arguments
n
Number of draws for inverse gamma distribution
n0
Prior sample size
var0
Prior variance
x
Vector with numeric values for density evaluation
Author(s)
Alexander Robitzsch
References
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A.,
& Rubin, D. B. (2014).
Bayesian data analysis (Vol. 3). Boca Raton, FL, USA: Chapman & Hall/CRC.
See Also
MCMCpack::rinvgamma
Examples
#############################################################################
# EXAMPLE 1: Inverse gamma distribution
#############################################################################
# prior sample size of 100 and prior variance of 1.5
n0 <- 100
var0 <- 1.5
# 100 random draws
y1 <- rinvgamma2( n=100 , n0 , var0 )
summary(y1)
graphics::hist(y1)
# density
x <- seq( 0 , 2 , len=100 )
plot( x , dinvgamma2( x , n0 , var0 ) , type="l")