Learn the difference between linear regression and multiple regression and how investors can use these types of statistical analysis.

This paper studies sparse linear regression analysis with outliers in the responses. A parameter vector for modeling outliers is added to the standard linear regression model and then the sparse ...

A sequential regression or chained equations imputation approach uses a Gibbs sampling-type iterative algorithm that imputes the missing values using a sequence of conditional regression models. It is ...

Using Linear Regression Because much economic data has cycles, multiple trends and non-linearity, simple linear regression is often inappropriate for time-series work, according to Yale University.