In Bayesian reasoning, if two distributions for the same parameter are normal, then their combination is too; its mean is the average of the two primary means, weighting by the respective precisions (inverse variances).
I think this refers to the inverse-variance method. I am not sure under which conditions it should be applied, but it minimises the variance of a weighted mean of 2 estimates of the same variable of interest.
I think this refers to the inverse-variance method. I am not sure under which conditions it should be applied, but it minimises the variance of a weighted mean of 2 estimates of the same variable of interest.