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DOE OSTI · 1337112

Influence plots for LASSO

Jang, Dae -Heung·Anderson-Cook, Christine Michaela
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Abstract

With many predictors in regression, fitting the full model can induce multicollinearity problems. Least Absolute Shrinkage and Selection Operation (LASSO) is useful when the effects of many explanatory variables are sparse in a high-dimensional dataset. Influential points can have a disproportionate impact on the estimated values of model parameters. Here, this paper describes a new influence plot that can be used to increase understanding of the contributions of individual observations and the robustness of results. This can serve as a complement to other regression diagnostics techniques in the LASSO regression setting. Using this influence plot, we can find influential points and their impact on shrinkage of model parameters and model selection. Lastly, we provide two examples to illustrate the methods.

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97 MATHEMATICS AND COMPUTINGLASSO influence plotLASSO plotinfluential observationsleast absolute shrinkage and selection operationmathematics

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Jang, Dae -Heung, Anderson-Cook, Christine Michaela. 2016-11-22. Influence plots for LASSO. https://doi.org/10.1002/qre.2106

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