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 ...

We introduce a fast stepwise regression method, called the orthogonal greedy algorithm (OGA), that selects input variables to enter a p-dimensional linear regression model (with p ≫ n, the sample size ...

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 ...

Edmilson Rodrigues Pinto, Leandro Alves Pereira, On variable selection in joint modeling of mean and dispersion, Brazilian Journal of Probability and Statistics, Vol. 35, No. 4 (2021), pp. 875-894 ...

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