Lower confidence bounds for prediction accuracy in high dimensions via AROHIL Monte Carlo
نویسندگان
چکیده
منابع مشابه
Lower confidence bounds for prediction accuracy in high dimensions via AROHIL Monte Carlo
MOTIVATION Implementation and development of statistical methods for high-dimensional data often require high-dimensional Monte Carlo simulations. Simulations are used to assess performance, evaluate robustness, and in some cases for implementation of algorithms. But simulation in high dimensions is often very complex, cumbersome and slow. As a result, performance evaluations are often limited,...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2011
ISSN: 1460-2059,1367-4803
DOI: 10.1093/bioinformatics/btr542