### Abstract

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 language | English (US) |
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Pages (from-to) | 515-522 |

Number of pages | 8 |

Journal | Journal of Optimization Theory and Applications |

Volume | 127 |

Issue number | 3 |

DOIs | |

State | Published - Dec 1 2005 |

### Keywords

- 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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## Cite this

Kalaba, R. E., Johnson, J., & Natsuyama, H. H. (2005). Statistical measures for least squares using the αQβR algorithm.

*Journal of Optimization Theory and Applications*,*127*(3), 515-522. https://doi.org/10.1007/s10957-005-7499-4