Variance Inflation Factor Calculator
Check how strongly one explanatory variable is predictable from the other explanatory variables. The tool shows the method and key assumptions so you can inspect how the input values lead to the estimate.
How to use this calculator
- Enter r² for predictor regressed on other predictors using the unit and definition shown beside the input.
- Check that all values refer to the same time period and scenario.
- Review the outputs alongside the assumptions before using them in a decision.
Formula and assumptions
VIF=1/(1−R²).
- The estimate uses an R² value from an auxiliary regression. VIF thresholds are rules of thumb, not universal pass/fail limits; interpretation depends on the model and domain.
- The estimate is calculated from values you enter. It does not connect to external accounts, obtain live prices, or validate local regulations or engineering specifications.
Worked examples
Worked example
For R²=0.72, VIF=1/(1−0.72)≈3.57.
Enter an auxiliary-regression R² between 0 and 1, excluding exactly 1.
Investigate multicollinearity with the full model context rather than a single threshold.
Understanding the result
The estimate uses an R² value from an auxiliary regression. VIF thresholds are rules of thumb, not universal pass/fail limits; interpretation depends on the model and domain.
Change one input at a time to see how sensitive the output is to that assumption.
Important notes
The estimate uses an R² value from an auxiliary regression. VIF thresholds are rules of thumb, not universal pass/fail limits; interpretation depends on the model and domain.
Frequently asked questions
What formula does the Variance Inflation Factor Calculator use?
VIF=1/(1−R²).
What should I verify before relying on the result?
The estimate uses an R² value from an auxiliary regression. VIF thresholds are rules of thumb, not universal pass/fail limits; interpretation depends on the model and domain.
Can I compare different scenarios?
Yes. Change one assumption at a time, keep units and definitions consistent, and save the inputs used for each comparison.
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This page provides a calculation tool plus explanatory information so you can understand what the result means and when the underlying method may not fit your situation.