Bias/Variance Decompositions for Likelihood-Based Estimators.
The bias/variance decomposition of mean-squared error is well understood and relatively straightforward. In this note, a similar simple decomposition is derived, valid for any kind of error measure that, when using the appropriate probability model, can be derived from a Kullback-Leibler divergence or log-likelihood.
Heskes
T
University of Nijmegen, Foundation for Neural Networks, Nijmegen, NL, Geert Grooteplein 21, 6525 EZ. tom@mbfys.kun.nl