New information criteria revolutionize model selection in linear regression.
The goal of the study was to find the best model among several options by using information criteria. These criteria help to see how well a model fits the data while keeping it simple. The researchers modified existing criteria and tested them in simulations and real-life examples. They found that these modified criteria can help choose the most accurate and simple model for a given dataset.