Calculate AIC by Hand
Expert Guide to Calculating AIC by Hand
Introduction & Importance
Calculating Akaike Information Criterion (AIC) by hand is crucial for model selection and understanding the trade-off between complexity and goodness of fit…
How to Use This Calculator
- Enter the number of parameters (k) in your model.
- Enter the log-likelihood (L) of your model.
- Click ‘Calculate’.
Formula & Methodology
The AIC formula is: AIC = 2k – 2L + p(k), where p(k) is a penalty term…
Real-World Examples
| Model | k | L | AIC |
|---|---|---|---|
| Linear | 2 | 12.5 | -17.0 |
| Quadratic | 3 | 13.2 | -15.4 |
Data & Statistics
| Model | k | L | AIC | ΔAIC |
|---|---|---|---|---|
| Linear | 2 | 12.5 | -17.0 | 0 |
| Quadratic | 3 | 13.2 | -15.4 | 1.6 |
Expert Tips
- Consider using AICc for small sample sizes.
- Remember, AIC is not a test statistic; it’s a measure of model quality.
Interactive FAQ
What is AIC?
AIC is a measure of the quality of a statistical model…