Risk glossary

 

Calibration

In statistics, calibration is the process of adjusting the values of the parameters of a parametric model to ensure the model will output data that, for a given set of input data, matches as closely as possible data found empirically. A danger of using too many parameters is that the model will fit the empirical data too well, meaning the model will not accurately predict results for a different set of input data. This is known as overfitting.

Click here for articles on calibration. 

  • LinkedIn  
  • Save this article
  • Print this page  

You need to sign in to use this feature. If you don’t have a Risk.net account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an indvidual account here: