Density, cumulative distribution function and random generation for inverse-gamma distribution.
Usage
density_inverse_gamma(shape, scale, x)
cdf_inverse_gamma(shape, scale, x)
random_inverse_gamma(shape, scale, n)Value
numeric vector
Functions density_XXX and cdf_XXX return numeric vectors of same length as x.
Function random_XXX returns a numeric vector of length n.
Examples
# Probability density function for an Inverse Gamma distribution
z <-density_inverse_gamma(shape = 1, scale = 2,x=.001 * seq(0, 300, 1))
# Computing the probability that the random variable X following an Inverse Gamma distribution
# with shape 1 and scale 2 is lower than x
z<-cdf_inverse_gamma(shape = 1, scale = 2, x = 1:10)
z
#> [1] 0.1353353 0.3678794 0.5134171 0.6065307 0.6703200 0.7165313 0.7514773
#> [8] 0.7788008 0.8007374 0.8187308
# Generating a random vector with each component drawn from an Inverse Gamma distribution
# with shape 1 and scale 2
z<- random_inverse_gamma(shape = 1, scale = 2, n = 10)
z
#> [1] 1.8595755 3.5026768 0.9455671 1.7850095 3.9711251 0.5509591
#> [7] 0.9329390 4.3234331 3.5199755 12.5092925