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Local asymptotic coding and the minimum description length
1999
IEEE Transactions on Information Theory
Common approximations for the minimum description length (MDL) criterion imply that the cost of adding a parameter to a model fit to n observations is about (1/2) log n bits. While effective for parameters which are large on a standardized scale, this approximation overstates the parameter cost near zero. A uniform approximation and local asymptotic argument show that the addition of a small parameter which is about two standard errors away from zero produces a model whose description length is
doi:10.1109/18.761287
fatcat:7ndhb3yslnetdhbr4gsjhmwcpy