Bayesian structural time series modeling

I don’t know that we have a case study on this reparameterization of an AR(1) process, but is all the same fundamental idea: Try to make things as independent as possible. If you do a random walk in levels, there is a lot of dependence between the current time point and the previous one. But if you parameterize in terms of innovations, then they are plausibly independent.