Release v0.2.13

multimput 0.2.13

• aggregate_impute() handles the corner case when join results in an empty
  dataset.
• The model_fun argument of model_impute() can be either a function or a
  string containing the name of a function (like "glm").
  Include the package name in case the function is not available in base R (like
  "INLA::inla").

Release v0.2.12

* `impute()` gains an `extra` argument.

  Use it for observations not in the model that you still want to add in the
  follow-up analysis.
  For example: exclude rare observations from the model but you want them in the
  aggregations.
* `impute()` on INLA models now also handles the binomial, the zero-inflated
  Poison (type 0 and 1) and the zero-inflated negative binomial (type 0 and 1)
  distributions.
* Add `hurdle_impute()` to fit a hurdle model based on a model of the presences
  and a model of the counts.
* Added validation rules for `rawImputed` and `aggregatedImputed` objects.
* Update [`checklist`](https://inbo.github.io/checklist/) infrastructure.

Release v0.2.11

# multimput 0.2.11

* Vignette runs without INLA.
  Required to make the package build on https://inbo.r-universe.dev

Release v0.2.10

# multimput 0.2.10

* Use checklist infrastructure. 

# multimput 0.2.7.9000

* `aggregate_impute()` now also works on `aggregatedImputed` objects (#34)

Version 0.2.9

Add support for the Gaussian and gamma distribution

v0.2.8.1

Merge pull request #36 from inbo/bugfix

Bugfix

v0.2.8

Merge pull request #35 from inbo/appveyor

Add AppVeyor support

version 0.2.7.9000

Merge pull request #34 from inbo/aggregate

add a method for `aggregate_impute()` for `aggregatedImputed` objects

Version 0.2.7

Merge pull request #33 from inbo/dplyr-update

Dplyr update

Version 0.2.6

Merge pull request #31 from inbo/hotfix

Some urgent bugfixes