I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems. Logistic regression is a technique used to make ...

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 ...

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

This is a preview. Log in through your library . Abstract We provide a remedy for two concerns that have dogged the use of principal components in regression: (i) principal components are computed ...

Predicting the affinity profiles of nucleic acid–binding proteins directly from the protein sequence is a challenging problem. We present a statistical approach for learning the recognition code of a ...

Regression quantiles can be substantially biased when the covariates are measured with error. In this paper we propose a new method that produces consistent linear ...