multimput 0.2.14

In case all imputed values are identical, model_impute() only runs a single model on one imputation. It reports the mean and standard errors based on the single model as-is.
model_impute() handles empty data.
model_impute() can filter the covariates with a user supplied function.
model_impute() gains a timeout argument.
Bugfix in generating zero-inflated negative binomial data.

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").

multimput 0.2.12

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 infrastructure.

multimput 0.2.11

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

multimput 0.2.10

Use checklist infrastructure.

multimput 0.2.7.9000

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