Predictions, Lasso Regression, Model Averaging, Spline Regression, Crossvalidation.
noise. The aim of the linear regression is to find the line that best fits the data in order to provide predicted values ŷ. Response = intercept + parameter*predictor + error Using maximum likelihood, the endeavor of finding the ‘best’ line is an iterative procedure. Perhaps the other most