Consider the regression model Y = h(x)+ε, where h is an unknown smooth regression function and ε is a random error with unknown distribution. To estimate the ...

Although [Vitor Fróis] is explaining linear regression because it relates to machine learning, the post and, indeed, the topic have wide applications in many things that we do with electronics and ...

Regression models with interaction effects have been widely used in multivariate analysis to improve model flexibility and prediction accuracy. In functional data analysis, however, due to the ...