- Bugfix in
hurdle_impute()when selecting single covariates.
- 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 atimeoutargument.- Bugfix in generating zero-inflated negative binomial data.
aggregate_impute()handles the corner case whenjoinresults in an empty dataset.- The
model_funargument ofmodel_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").
impute()gains anextraargument. 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
rawImputedandaggregatedImputedobjects. - Update
checklistinfrastructure.
- Vignette runs without INLA. Required to make the package build on https://inbo.r-universe.dev
- Use
checklistinfrastructure.
aggregate_impute()now also works onaggregatedImputedobjects (#34)