This article is concerned with the selection of subsets of predictor variables in a linear regression model for the prediction of a dependent variable. It is based on a Bayesian approach, intended to ...

It is possible to perform linear regression analyses using R in situations where the variable of interest is categorical. However, in my opinion, there are other techniques that are preferable in such ...

Linear regression and feature selection are two such foundational topics. Linear regression is a powerful technique for predicting numbers from other data.

This tells R to find the best model in which the response variable y is a linear function of a set of explanatory variables x1, x2, and so on. I will start with a model I call “model.ks” (to denote an ...

Regression analysis is a quantitative tool that is easy to use and can provide valuable information on financial analysis and forecasting.

This is a preview. Log in through your library . Abstract Shibata (1981, "Biometrika" 68, 45-54) considers data-generating mechanisms belonging to a certain class of linear regressions with errors ...