CorrCombo S4 class

Holds the result of corrSelect or MatSelect: a list of valid variable combinations and their correlation statistics.

This class stores all subsets of variables that meet the specified correlation constraint, along with metadata such as the algorithm used, correlation method(s), variables forced into every subset, and summary statistics for each combination.

Usage

# S4 method for class 'CorrCombo'
show(object)

Arguments

object

A CorrCombo object to be printed.

Slots

subset_list

A list of character vectors. Each vector is a valid subset (variable names).

avg_corr

A numeric vector. Average absolute correlation within each subset.

min_corr

A numeric vector. Minimum pairwise absolute correlation in each subset.

max_corr

A numeric vector. Maximum pairwise absolute correlation within each subset.

names

Character vector of all variable names used for decoding.

threshold

Numeric scalar. The correlation threshold used during selection.

forced_in

Character vector. Variable names that were forced into each subset.

search_type

Character string. One of "els" or "bron-kerbosch".

cor_method

Character string. Either a single method (e.g. "pearson") or "mixed" if multiple methods used.

n_rows_used

Integer. Number of rows used for computing the correlation matrix (after removing missing values).

See also

corrSelect, MatSelect, corrSubset

Examples

show(new("CorrCombo",
  subset_list = list(c("A", "B"), c("A", "C")),
  avg_corr = c(0.2, 0.3),
  min_corr = c(0.1, 0.2),
  max_corr = c(0.3, 0.4),
  names = c("A", "B", "C"),
  threshold = 0.5,
  forced_in = character(),
  search_type = "els",
  cor_method = "mixed",
  n_rows_used = as.integer(5)
))