Universal Principles, Approximation and Model Choices

author: Lauri Davies, University of Duisburg-Essen
published: Feb. 25, 2007,   recorded: October 2005,   views: 2933

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


Universal principles are ones which make no reference to the subject matter of the data and include Maximum Likelihood, Bayes, AIC and MDL. In this talk we criticize the use of such principles to solve the problem of model choice. The criticism will be mainly directed against MDL but corresponding arguments can be made against the other principles. A concept of approximation will be introduced and its use in choosing a model illustrated by examples from non-parametric statistics.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: