Extendable MDL

In this paper we show that a combination of the minimum description length principle and an exchange-ability condition leads directly to the use of Jeffreys prior. This approach works in most cases even when Jeffreys prior cannot be normalized. Kraft´s inequality links codes and distributions but a closer look at this inequality demonstrates that this link only makes sense when sequences are considered as prefixes of potential longer sequences. For technical reasons only results for exponential families are stated. Results on when Jeffreys prior can be normalized after conditioning on a initializing string are given. An exotic case where no initial string allow Jeffreys prior to be normalized is given and some way of handling such exotic cases are discussed.