toy: Toy dataframe with varying levels of multicollinearity

In collinear: Automated Multicollinearity Management

Toy dataframe with varying levels of multicollinearity

Description

Dataframe with known relationship between responses and predictors useful to illustrate multicollinearity concepts.

Usage

data(toy)

Format

dataframe with 2000 rows and 5 columns.

Details

Columns:

• y: response variable generated from a * 0.75 + b * 0.25 + noise.

• a: most important predictor of y, uncorrelated with b.

• b: second most important predictor of y, uncorrelated with a.

• c: generated from a + noise.

• d: generated from (a + b)/2 + noise.

These are variance inflation factors of the predictors in toy. variable vif b 4.062 d 6.804 c 13.263 a 16.161

See Also

Other example_data: vi, vi_predictors, vi_predictors_categorical, vi_predictors_numeric, vi_responses, vi_smol

collinear documentation built on Dec. 8, 2025, 5:06 p.m.