Optimal cross-validation in density estimation with the $L^{2}$-loss
Optimal cross-validation in density estimation with the $L^{2}$-loss
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Publisher
The Institute of Mathematical Statistics
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Language
English
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The Institute of Mathematical Statistics
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Contents
We analyze the performance of cross-validation (CV) in the density estimation framework with two purposes: (i) risk estimation and (ii) model selection. The main focus is given to the so-called leave-p-out CV procedure (Lpo), where p denotes the cardinality of the test set. Closed-form expressions are settled for the Lpo estimator of the risk of pr...
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Full title
Optimal cross-validation in density estimation with the $L^{2}$-loss
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TN_cdi_projecteuclid_primary_oai_CULeuclid_euclid_aos_1410440628
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_projecteuclid_primary_oai_CULeuclid_euclid_aos_1410440628
Other Identifiers
ISSN
0090-5364
E-ISSN
2168-8966
DOI
10.1214/14-AOS1240
