Gaussian Mixture Model Calculator
Fit a mixture of Gaussian distributions to your data using the EM algorithm.
Model Summary
Data Points:10
Components:2
Iterations:5
Parameters:5
Component Parameters
| Component | Weight | Mean | Std Dev | Variance | Size |
|---|---|---|---|---|---|
| 1 | 60.1% | 2.4533 | 0.9230 | 0.8519 | 6 |
| 2 | 39.9% | 5.8755 | 0.2584 | 0.0668 | 4 |
Model Fit
Log-Likelihood:-14.9894
AIC:39.9788
BIC:41.4917
Mixture Density
Solid: Mixture | Dashed: Components | Dots: Data colored by assignment
Interpretation
The data is modeled as a mixture of 2 Gaussian distributions. Lower AIC/BIC values indicate better model fit. Compare different numbers of components to find the optimal model.