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Linear Programming pp 165–184Cite as

Regression

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 196))

Abstract

In this chapter, we shall study an application of linear programming to an area of statistics called regression. As a specific example, we shall use size and iteration-count data collected from a standard suite of linear programming problems to derive a regression estimate of the number of iterations needed to solve problems of a given size.

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Notes

  1. 1.

    “Average” is usually taken as synonymous with “mean” but in this section we shall use it in an imprecise sense, employing other technically defined terms for specific meanings.

  2. 2.

    Recall from calculus that a critical point is any point at which the derivative vanishes or fails to exist.

  3. 3.

    In the social sciences, a fundamental difficulty is the lack of specific arguments validating the appropriateness of the models commonly introduced.

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    Robert J. Vanderbei

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Vanderbei, R.J. (2014). Regression. In: Linear Programming. International Series in Operations Research & Management Science, vol 196. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-7630-6_12

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