I'm trying to fit a multiple linear regression model to my data with couple of input parameters, say 3.

I was just wondering why regression problems are called "regression" problems. What is the story behind the name? One definition for regression: "Relapse to a less perfect or developed state."

Dec 4, 2014 · When we say, to regress Y Y against X X, do we mean that X X is the independent variable and Y the dependent variable? i.e. Y = aX + b Y = a X + b.

Oct 19, 2011 · LASSO regression is a type of regression analysis in which both variable selection and regulization occurs simultaneously. This method uses a penalty which affects they value …

I am trying to perform a multiple regression in R. However, my dependent variable has the following plot: Here is a scatterplot matrix with all my variables (WAR is the dependent …

Feb 10, 2023 · What would be a "reasonable" minimal number of observations to look for a trend over time with a linear regression? what about fitting a quadratic model? I work with composite …

Sample size calculation for logistic regression is a complex problem, but based on the work of Peduzzi et al. (1996) the following guideline for a minimum number of cases to include in your …

Oct 3, 2021 · Although one can compute a single regression for all data points, if you include model assumptions such as i.i.d. normal errors, the model for all points combined can't be …

Consequently, the solution of the Normal equations will immediately become possible and it will rapidly become numerically stable as $\nu$ increases from $0$. This description of the …

Jun 10, 2016 · I am experimenting with stepwise regression for the sake of diversity in my approach to the problem. So, I have 2 questions: What are the advantages of stepwise …