Description

Provides tools for determining estimability of linear functions of regression coefficients, and alternative epredict methods for lm, glm, and mlm objects that handle non-estimable cases correctly.

Details

When a linear model is not of full rank, the regression coefficients are not uniquely estimable. However, the predicted values are unique, as are other linear combinations where the coefficients lie in the row space of the data matrix. Thus, estimability of a linear function of regression coefficients can be determined by testing whether the coefficients lie in this row space – or equivalently, are orthogonal to the corresponding null space.

This package provides functions nonest.basis and is.estble to facilitate such an estimability test. Package developers may find these useful for incorporating in their predict methods when new predictor settings are involved.

The function estble.subspace is useful for projecting a matrix onto an estimable subspace whose rows are all estimable.

The package also provides epredict methods – alternatives to the predict methods in the stats package for "lm", "glm", and "mlm" objects. When the newdata argument is specified, estimability of each new prediction is checked and any non-estimable cases are replaced by NA.

Author(s)

Russell V. Lenth <russell-lenth@uiowa.edu>

References

Monahan, John F. (2008) A Primer on Linear Models, CRC Press. (Chapter 3)