Statistical measures for ordinary least squares using the αQ algorithm

J. Johnson, R. E. Kalaba

Research output: Contribution to journalArticlepeer-review


This paper shows how the dynamic program algorithm called the αQ algorithm can be used as an alternative algorithm to produce the coefficients of a least squares problem. It shows also how the output of the 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 t statistics, and the F statistics. These quantities serve as a measure of how well the model fits the data.

Original languageEnglish (US)
Pages (from-to)461-474
Number of pages14
JournalJournal of Optimization Theory and Applications
Issue number3
StatePublished - Jun 1 2003


  • Optimal control
  • least squares
  • regression coefficient
  • statistical tests

ASJC Scopus subject areas

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


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