Statistical measures for least squares using the αQβR algorithm

R. E. Kalaba, J. Johnson, H. H. Natsuyama

Research output: Contribution to journalArticlepeer-review


This paper shows how the output derived from the α Qβ R algorithm can be used to calculate various statistical quantities needed to evaluate linear models. In particular, we show how to calculate standard statistical quantities like the coefficient of determination R 2, the F-statistics, and the t-statistics. These quantities serve as a measure of how well the model fits the data.

Original languageEnglish (US)
Pages (from-to)515-522
Number of pages8
JournalJournal of Optimization Theory and Applications
Issue number3
StatePublished - Dec 2005


  • Multicollinearity
  • Optimal control
  • Regression coefficients
  • Statistical tests

ASJC Scopus subject areas

  • Control and Optimization
  • Management Science and Operations Research
  • Applied Mathematics


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