where 𝑝( 𝐷 𝑟,𝑡 | | 𝜽 ) is the likelihood of observed data given parameters 𝜽 , 𝑝(𝜽) is the prior distribution of 𝜽, and the denominator ∫ 𝑝(𝐷 𝑟,𝑡 | 𝜽)𝑑𝜽 which normalizes the distribution is called evidence. Given the observation model in eq. ( ) and assuming that the observations are independent and identically distributed (i.i.d.), the likelihood is