Random draws and density of inverse gamma distribution parameterized in prior sample size n0 and prior variance var0 (see Gelman et al., 2014).

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

Value

A vector containing random draws or density values

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, stats::rgamma, MCMCpack::dinvgamma, stats::dgamma

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 <- sirt::rinvgamma2( n=100, n0, var0 )
summary(y1)
graphics::hist(y1)

# density y at grid x
x <- seq( 0, 2, len=100 )
y <- sirt::dinvgamma2( x, n0, var0 )
graphics::plot( x, y, type="l")