ensemble: Create bootstrapped ensembles of a model
In dtkaplan/statisticalModeling: Functions for Teaching Statistical Modeling

Create bootstrapped ensembles of a model

1	ensemble(mod, nreps = 2, data = NULL)

`mod`	a model whose data will be used for resampling
`nreps`	how many resampling trials should be created
`data`	a data table to use for resampling. This is not needed for many common model types, such as `lm`, `glm`, etc. See details.

The approach to bootstrapping implemented by this function is to create a set of bootstrap trials all in one go. Then, other functions such as effect_size and evaluate_model() will be used to extract the information from each of the bootstrap replicates. Many model types in R carry the data used to train the model as part of the model object produced. For these types of models, e.g. lm and glm, there is no need to provide a value for the data argument. But there are some types of models for which the training data cannot be extracted from the model object. In such situations, you use data = to provide the data set to use for resampling.