We explore large-scale functional linear regression in which the scalar response is associated with a potentially ultrahigh number of functional predictors, leading to a more challenging model ...

A semi-parametric generalization of the proportional hazards regression model is defined, whereby the hazard functions can cross for different values of the covariates. In the two-sample comparison, ...

Delta-p statistics is an easier means of communicating results to a non-technical audience than the plain coefficients of a logistic regression model. In this article, authors Maarit Widmann and ...

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

Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of residuals, checking outliers. Practical hand on experience ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

Nonlinear regression is a form of regression analysis in which data fit to a model is expressed as a mathematical function.