2021/01/15 by Eichenlaub, Manuel M.
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Methodology (stat.ME)
paper · doi:10.48550/arxiv.2101.06289
In Bayesian inference, an unknown measurement uncertainty is often quantified in terms of a Gamma distributed precision parameter, which is impractical when prior information on the standard deviation of the measurement uncertainty shall be utilised during inference. This paper thus introduces a method for transforming between a gamma distributed precision parameter and the distribution of the associated standard deviation. The proposed method is based on numerical optimisation and shows adequate results for a wide range of scenarios.