In this paper linear restrictions on regression coefficients are studied. Let the p × q2 matrix of coefficients of regression of the p dependent variates on q2 of the independent variates be $\mathbf{ ...

Cun-Hui Zhang, Jian Huang, The Sparsity and Bias of the Lasso Selection in High-Dimensional Linear Regression, The Annals of Statistics, Vol. 36, No. 4 (Aug., 2008), pp. 1567-1594 ...

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Akur8 released today a new research paper for the actuarial community entitled “Credibility and Penalized Regression.” Developed by a senior team of a ...

Variable imputation was performed by polytomous regression (unordered categorical variables), LR (binary variables), and Bayesian linear regression (continuous variables). Multiple (m = 5) imputation ...

One useful tool to help us make sense of these kinds of problems is regression. Regression is a statistical method that allows us to look at the relationship between two variables, while holding other ...