Inference with Linear Equality and Inequality Constraints Using R: The Package ic.infer
AbstractIn 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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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Statistical Software.
Volume (Year): 33 ()
Issue (Month): i10 ()
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- Ulrike Groemping, . "Relative Importance for Linear Regression in R: The Package relaimpo," Journal of Statistical Software, American Statistical Association, vol. 17(i01).
- 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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