4.5 Limitations

Jeffreys priors can be applied to multi-dimensional models (based on a joint density), but the results are not as reliable.

Intuitively, the multi-dimensional Jeffreys Prior still contains a considerable amount of information about the expected value of parameter. The area surrounded by the axis and the pdf is at infinite distance, which means we’d expect the parameter to lie further away from \(0\).