Model Selection and the Principle of Minimum Description Length

@article{Hansen2001ModelSA,
  title={Model Selection and the Principle of Minimum Description Length},
  author={M. Hansen and Bin Yu},
  journal={Journal of the American Statistical Association},
  year={2001},
  volume={96},
  pages={746 - 774}
}
  • M. Hansen, Bin Yu
  • Published 2001
  • Mathematics
  • Journal of the American Statistical Association
This article reviews the principle of minimum description length (MDL) for problems of model selection. By viewing statistical modeling as a means of generating descriptions of observed data, the MDL framework discriminates between competing models based on the complexity of each description. This approach began with Kolmogorov's theory of algorithmic complexity, matured in the literature on information theory, and has recently received renewed attention within the statistics community. Here we… Expand
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