spatialsample has functions to create resamples of a spatial data set that can be used to evaluate models or to estimate the sampling distribution of some statistic. It is a specialized package designed with the same principles and terminology as rsample.


  • A resample is the result of a split of a data set. For example, in cross-validation, a data set is split into complementary subsets, and different partitions of subsets are used for different purposes. The data structure rsplit is used to store a single resample.

  • When the data are split in two, the portion that is used to estimate the model or calculate the statistic is called the analysis set here. In machine learning this is sometimes called the "training set", but this may be a poor name choice in a resampling context since it might conflict with an initial split of the original data.

  • Conversely, the other data in the split are called the assessment data. In bootstrapping, these data are often called the "out-of-bag" samples.

  • A collection of resamples is contained in an rset object.

Basic Functions

The main resampling functions are: spatial_clustering_cv()