The generalized Beta distribution βτ(c,d,κ) is a continuous distribution on (0,1) with density function proportional to uc−1(1−u)d−1(1+(τ−1)u)κ,u∈(0,1), with parameters c>0, d>0, κ∈R and τ>0.
The (scaled) generalized Beta prime distribution β′τ(c,d,κ,σ) is the distribution of the random variable σ×U1−U where U∼βτ(c,d,κ).
Assume a βτ(c,d,κ) prior distribution is assigned to the success probability parameter θ of the binomial model with n trials. Then the posterior distribution of θ after x successes have been observed is (θ∣x)∼βτ(c+x,d+n−x,κ).
Let the statistical model given by two independent observations x∼P(λT),y∼P(μS), where S and T are known design parameters and μ and λ are the unknown parameters.
Assign the following independent prior distributions on μ and ϕ:=λμ (the relative risk): μ∼G(a,b),ϕ∼β′(c,d,σ), where G(a,b) is the Gamma distribution with shape parameter a and rate parameter b, and β′(c,d,σ) is the scaled Beta prime distribution with shape parameters c and d and scale σ, that is the distribution of the random variable σ×U1−U where U∼β(c,d).
Then the posterior distribution of ϕ is (ϕ∣x,y)∼β′ρ/σ(c+x,a+d+y,c+d,ρ) where ρ=b+TS.