SLAW is a procedure that derives representative scaling laws of a process from sensitivity analysis experimental data. The approach integrates dimensional analysis into the multivariate linear regression backwards elimination procedure. In addition to the scaling laws, the program provides a set of dimensionless groups ranked by relevance. The algorithm is coded in 6 Matlab .m files and also has a java interface.

CITATION: "SLAW, a package for Scaling LAWs from statistical data," P. Mendez and F. Ordóñez, 2004. Last modified 08/14/05.

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For a detailed description of the methodology and for example applications of the algorithm to pendulum motion, metal to ceramic joining, and "punch test" data, see:

Mendez, P.F. and Ordonez, F., "Scaling Laws from Statistical Data and Dimensional Analysis," Journal of Applied Mechanics, 2005. 72 (5): p. 648-657.

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