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Inference with Linear Equality and Inequality Constraints Using R: The Package ic.infer

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  • Grömping, Ulrike

Abstract

In linear models and multivariate normal situations, prior information in linear inequality form may be encountered, or linear inequality hypotheses may be subjected to statistical tests. R package ic.infer has been developed to support inequality-constrained estimation and testing for such situations. This article gives an overview of the principles underlying inequality-constrained inference that are far less well-known than methods for unconstrained or equality-constrained models, and describes their implementation in the package.

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  • Grömping, Ulrike, 2010. "Inference with Linear Equality and Inequality Constraints Using R: The Package ic.infer," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i10).
    • Handle: RePEc:jss:jstsof:v:033:i10
    DOI: http://hdl.handle.net/10.18637/jss.v033.i10
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    1. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521471626, January.
    2. Groemping, Ulrike, 2006. "Relative Importance for Linear Regression in R: The Package relaimpo," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 17(i01).
    3. Gromping, Ulrike, 2007. "Estimators of Relative Importance in Linear Regression Based on Variance Decomposition," The American Statistician, American Statistical Association, vol. 61, pages 139-147, May.
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