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Relative Importance for Linear Regression in R: The Package relaimpo

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  • Ulrike Groemping
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    Abstract

    Relative importance is a topic that has seen a lot of interest in recent years, particularly in applied work. The R package relaimpo implements six different metrics for assessing relative importance of regressors in the linear model, two of which are recommended - averaging over orderings of regressors and a newly proposed metric (Feldman 2005) called pmvd. Apart from delivering the metrics themselves, relaimpo also provides (exploratory) bootstrap confidence intervals. This paper offers a brief tutorial introduction to the package. The methods and relaimpo's functionality are illustrated using the data set swiss that is generally available in R. The paper targets readers who have a basic understanding of multiple linear regression. For the background of more advanced aspects, references are provided.

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    Article provided by American Statistical Association in its journal Journal of Statistical Software.

    Volume (Year): 17 ()
    Issue (Month): i01 ()
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    Handle: RePEc:jss:jstsof:17:i01

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    Cited by:
    1. Hüttner, Frank & Sunder, Marco, 2011. "Decomposing R2 with the Owen value," Working Papers 100, University of Leipzig, Faculty of Economics and Management Science.
    2. Mitze, Timo & Reinkowski, Janina, 2010. "Testing the Validity of the Neoclassical Migration Model: Overall and Age-Group Specific Estimation Results for German Spatial Planning Regions," MPRA Paper 23616, University Library of Munich, Germany.
    3. Ulrike Grömping, . "Inference with Linear Equality and Inequality Constraints Using R: The Package ic.infer," Journal of Statistical Software, American Statistical Association, vol. 33(i10).

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