Comment by jampekka
3 months ago
At least in the mathematically simpler scenario of a gaussian prior and gaussian observations, the posterior mean is computed by weighing by the the inverses of variances (aka precisions) just like this.
3 months ago
At least in the mathematically simpler scenario of a gaussian prior and gaussian observations, the posterior mean is computed by weighing by the the inverses of variances (aka precisions) just like this.
To add, for anyone who's followed the link - that's entries numbers 1 and 2, or "Normal with known variance σ²" and Normal with known precision τ", under "When likelihood function is a continuous distribution".
Also, note that the "precision" τ is defined as 1/σ².