Abstract: The article is devoted to thorough study of a new regression method performance. The proposed method based on convex correcting procedures over sets of predictors is subject to modifications and tested in comparison with the acknowledged regression utility. The modifications touch both resource consumption and quality aspects of the method and tests are performed with sets of generated samples.

Keywords: forecasting, bias-variance decomposition, convex combinations, variables selection.

ACM Classification Keywords: G.3 Probability and Statistics - Correlation and regression analysis, Statistical computing.

Link:

ON SOME PROPERTIES OF REGRESSION MODELS BASED ON CORRELATION MAXIMIZATION OF CONVEX COMBINATIONS

Oleg Senko, Alexander Dokukin

http://www.foibg.com/ijima/vol01/ijima01-2-p02.pdf