Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

A general nonlinear regression problem is considered with measurement error in the predictors. We assume that the response is related to an unknown linear combination ...

A new graphical method for assessing parametric transformations of the response in linear regression is given. We simply regress the response variable Y on the predictors, find the fitted values, and ...

The bregr package provides a streamlined, modular workflow for batch regression modeling. The process begins with installation and initialization, followed by core modeling steps such as setting ...

A machine learning framework can distinguish molecules made by biological processes from those formed through non-biological ...