- A
`nonest.basis()`

function is provided that determines a basis for the null space of a matrix. This may be used in conjunction with`is.estble()`

to determine the estimability (within a tolerance) of a given linear function of the regression coefficients in a linear model. - A set of
`epredict()`

methods are provided for`lm`

,`glm`

, and`mlm`

objects. These work just like`predict()`

, except an`NA`

is returned for any cases that are not estimable. This is a useful alternative to the generic warning that “predictions from rank-deficient models are unreliable.” - A function
`estble.subspace()`

that projects a set of linear functions onto an

estimable subspace (possibly of smaller dimension). This can be useful in creating a set of estimable contrasts for joint testing. - Package developers may wish to import this package and incorporate estimability checks for their
`predict`

methods.

To install latest version from CRAN, run

`install.packages("estimability")`

Release notes for the latest CRAN version are found at https://cran.r-project.org/package=estimability/NEWS – or do

`news(package = "estimability")`

for notes on the version you have installed.To install the latest development version from Github, have the newest

**devtools**package installed, then run`devtools::install_github("rvlenth/estimability", dependencies = TRUE)`

For latest release notes on this development version, see the NEWS file