WeightIt (version 0.8.0)

make_full_rank: Make a matrix full rank

Description

When writing user-defined methods for use with weightit, it may be necessary to take the potentially non-full rank covs data frame and make it full rank for use in a downstream function. This function performs that operation.

Usage

make_full_rank(mat,
               with.intercept = TRUE)

Arguments

mat

a numeric matrix or data frame to be transformed. Typically this contains covariates. NAs are not allowed.

with.intercept

whether an intercept (i.e., a vector of 1s) should be added to mat before making it full rank. If TRUE, the intercept will be used in determining whether a column is linearly dependent on others. Regardless, no intercept will be included in the output.

Value

An object of the same type as mat containing only linearly independent columns.

Details

make_full_rank makes a matrix full rank by removing columns one at a time and determining whether the rank of the matrix changes. If it does not, that column is deleted. First, all columns that only contain one value are deleted. Then, if with.intercept is set to TRUE, an intercept column is added to the matrix. After determining which columns can be removed without changing the rank of the matrix, a matrix is returned with only those columns (and not the added intercept).

See example at method_user.

See Also

method_user, model.matrix

Examples

# NOT RUN {
set.seed(1000)
c1 <- rbinom(10, 1, .4)
c2 <- 1-c1
c3 <- rnorm(10)
c4 <- 10*c3
mat <- data.frame(c1, c2, c3, c4)

make_full_rank(mat) #leaves c2 and c4

make_full_rank(mat, with.intercept = FALSE) #leaves c1, c2, and c4
# }