Abstract
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 R2, the t statistics, and the F statistics. These quantities serve as a measure of how well the model fits the data.
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Johnson, J., Kalaba, R. Statistical Measures for Ordinary Least Squares Using the αQ Algorithm. Journal of Optimization Theory and Applications 117, 461–474 (2003). https://doi.org/10.1023/A:1023937419543
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DOI: https://doi.org/10.1023/A:1023937419543