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lp_solve is a free software command line utility and library for solving linear programming and mixed integer programming problems. It ships with support for two file formats, MPS and lp_solve's own LP format. [1]
Linear least squares (LLS) is the least squares approximation of linear functions to data. It is a set of formulations for solving statistical problems involved in linear regression, including variants for ordinary (unweighted), weighted, and generalized (correlated) residuals.
IRLS is used to find the maximum likelihood estimates of a generalized linear model, and in robust regression to find an M-estimator, as a way of mitigating the influence of outliers in an otherwise normally-distributed data set, for example, by minimizing the least absolute errors rather than the least square errors.
The configuration linear program (configuration-LP) is a linear programming technique used for solving combinatorial optimization problems. It was introduced in the context of the cutting stock problem. [1] [2] Later, it has been applied to the bin packing [3] [4] and job scheduling problems.
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Linear programming (LP), also called linear optimization, is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements and objective are represented by linear relationships.
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A Primer of LISREL: Basic Applications and Programming for Confirmatory Factor Analytic Models. New York: Springer. ISBN 0-387-96972-1. Kelderman, Henk (1987). "LISREL models for inequality constraints in factor and regression analysis". In Cuttance, Peter; Ecob, Russell (eds.). Structural Modelling by Example.