This function performs multivariate regression partitioning using the mvpart R package (mvpart::mvpart()). It takes in a data frame of count data, a data frame of sample level information, and various optional arguments, and returns a list of outputs including the multivariate regression tree object, the change points, the partition assignments, and the number of groups.

mv_regression_partition(
  data_source_counts,
  data_source_levels,
  rand = 1000,
  transformation = c("chisq", "hellinger", "none")
)

Arguments

data_source_counts

Data frame with pollen data. Each row represents one level (sample) and each column represents one taxon. Table must contain sample_id column with unique values corresponding to data_source_levels

data_source_levels

Data frame with level ages, with each row representing one level (sample). The table must contain two columns: sample_id with unique values corresponding to data_source_levels, and age with ages of each level

rand

The number of times to randomly split the data to determine the optimal tree.

transformation

Selection of data transformation options. hellinger = Hellinger, chisq = Chisq, none = without transformation. Both Hellinger and Chisq are recommended for proportional/percentage data

Value

A list containing the following items:

  • mrt_resultThe multivariate regression tree object.

  • change_pointsThe change points in the regression tree.

  • partitionsThe partition assignments for each sample.

  • mrt_groupsThe number of groups in the partitioning.

  • mrt_groups_per_sampleThe number of groups per sample.

See also

mvpart::mvpart()