Balgobin Nandram, Erik Barry Erhardt, Fitting Bayesian Two-Stage Generalized Linear Models Using Random Samples via the SIR Algorithm, Sankhyā: The Indian Journal of Statistics (2003-2007), Vol. 66, ...

Linear regression draws corresponding trend lines, such as disease outbreaks, bitcoin prices, demand for software experts, etc.

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

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

An algorithm is presented for nonlinear least squares estimation in which the parameters to be estimated can be regarded as all nonlinear (the traditional approach) or reclassified as linear-nonlinear ...

Linear techniques include ordinary linear regression, L1 (lasso) and L2 (ridge) regression, and linear support vector regression (linear SVR). This article presents a demo of linear SVR, implemented ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the AdaBoost.R2 algorithm for regression problems (where the goal is to predict a single numeric value). The ...