Extract Variable Subsets from a CorrCombo Object

Extracts one or more variable subsets from a CorrCombo object as data frames. Typically used after corrSelect or MatSelect to obtain filtered versions of the original dataset containing only low‐correlation variable combinations.

Usage

corrSubset(res, df, which = "best", keepExtra = FALSE)

Arguments

res

A CorrCombo object returned by corrSelect or MatSelect.

df

A data frame or matrix. Must contain all variables listed in res@names. Columns not in res@names are ignored unless keepExtra = TRUE.

which

Subsets to extract. One of:

"best" (default) or 1: the top‐ranked subset.
A single integer (e.g. 2): the nth ranked subset.
A vector of integers (e.g. 1:3): multiple subsets.
"all": all available subsets.

Subsets are ranked by decreasing size, then increasing average correlation.

keepExtra

Logical. If TRUE, columns in df not in res@names (e.g., factors, characters) are retained. Defaults to FALSE.

Value

A data frame if a single subset is extracted, or a list of data frames if multiple subsets are extracted. Each data frame contains the selected variables (and optionally extras).

Note

A warning is issued if any rows contain missing values in the selected variables.

Examples

# Simulate input data
set.seed(123)
df <- as.data.frame(matrix(rnorm(100), nrow = 10))
colnames(df) <- paste0("V", 1:10)

# Compute correlation matrix
cmat <- cor(df)

# Select subsets using corrSelect
res <- corrSelect(cmat, threshold = 0.5)

# Extract the best subset (default)
corrSubset(res, df)

# Extract the second-best subset
corrSubset(res, df, which = 2)

# Extract the first three subsets
corrSubset(res, df, which = 1:3)

# Extract all subsets
corrSubset(res, df, which = "all")

# Extract best subset and retain additional numeric column
df$CopyV1 <- df$V1
corrSubset(res, df, which = 1, keepExtra = TRUE)