matlab AIC
时间: 2023-08-20 09:11:45 浏览: 50
AIC (Akaike Information Criterion) is a statistical measure used for model selection in the context of regression analysis. It provides a way to compare different models based on their goodness of fit and complexity.
In MATLAB, you can calculate the AIC for a regression model using the `aic` function from the Statistics and Machine Learning Toolbox. This function takes as input the residual sum of squares (RSS) and the number of parameters in the model.
Here is an example of how you can calculate AIC in MATLAB:
```matlab
% Assuming you have a regression model with RSS and p (number of parameters)
RSS = 100;
p = 5;
% Calculate AIC
aic_value = aic(RSS, p);
```
The lower the AIC value, the better the model. It balances the goodness of fit with the complexity of the model, penalizing models with a large number of parameters.