## glmnetUtils 1.1.8

- Skip some tests on 32-bit Solaris R-patched due to numerical
convergence issues.

## glmnetUtils 1.1.7

- Add some plotting options for
`plot.cva.glmnet`

:
`log.x`

controls whether to plot the X-axis (lambda) on the
log scale, and the legend can be omitted by setting either
`legend.x`

or `legend.y`

to
`NULL`

.
- Compatibility fixes for glmnet 4.1-1.

## glmnetUtils 1.1.6

- Update maintainer email address.

## glmnetUtils 1.1.5

- Fix handling of non-factor categorical predictors (from R 4.0, data
frames will not have character columns converted to factors by default).
The practical impact of this should be minor.

## glmnetUtils 1.1.4

- Fix printout of
`glmnet.formula`

object.

## glmnetUtils 1.1.3

- Support relaxed (non-regularised) fits in
`glmnet.formula`

and `cv.glmnet.formula`

(requires
glmnet 3.0 or later).
- Add a legend when plotting a
`cva.glmnet`

object.

## glmnetUtils 1.1.2

- Fixes a bug in the assignment of observations to crossvalidation
folds in
`cva.glmnet`

. The impact is most serious for small
datasets, where the number of observations per fold is relatively low.
If you are using this function, itâ€™s highly recommended you update the
package.

## glmnetUtils 1.1.1

- Fixes bug where
`nfolds`

argument was not being passed to
`glmnet::cv.glmnet`

.

## glmnetUtils 1.1

- Now allows interaction and expression terms without requiring
`use.model.frame=TRUE`

. This works in an additive fashion, ie
the formula `~ a + b:c + d*e`

is treated as consisting of
three terms, `a`

, `b:c`

and `d*e`

each
of which is processed independently of the others. A dot in the formula
includes all main effect terms, ie `~ . + a:b + f(x)`

expands
to `~ a + b + x + a:b + f(x)`

(assuming a, b and x are the
only columns in the data). Note that a formula like
`~ (a + b) + (c + d)`

will be treated as two terms,
`a + b`

and `c + d`

.
- The call component of a
`glmnet`

/`cv.glmnet`

object that uses the original matrix/vector interface is now
useful.
- You can now explicitly specify the vector of crossvalidation folds
(for the inner loop over lambda) when calling
`cva.glmnet`

.
- Correctly handle non-syntactic factor variables in a formula.

## glmnetUtils 1.0.2