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 ...

We present estimators for a well studied statistical estimation problem: the estimation for the linear regression model with soft sparsity constraints (l q constraint with 0 < q ≤ 1) in the ...

We introduce a non-parametric estimation of the trimmed regression by using the local linear method of a censored scalar response variable, given a functional covariate. The main result of this work ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. Many of Pew Research Center’s survey analyses show relationships between two ...

Description: Inference in simple and multiple linear regression, estimation of model parameters, testing and prediction. Residual analysis, diagnostics and remedial measures. Multicollinearity. Model ...

Now that you've got a good sense of how to "speak" R, let's use it with linear regression to make distinctive predictions. The R system has three components: a scripting language, an interactive ...