Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

Scaled sparse linear regression jointly estimates the regression coefficients and noise level in a linear model. It chooses an equilibrium with a sparse regression method by iteratively estimating the ...

Regression imputation is commonly used to compensate for item nonresponse when auxiliary data are available. It is common practice to compute survey estimators by treating imputed values as observed ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Last month we explored how to model a simple relationship between two variables, such as the dependence of weight on height 1. In the more realistic scenario of dependence on several variables, we can ...