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

For example, if X and Y are highly correlated, they could be replaced in a linear regression by X+Y and X-Y without changing the fit of the model or statistics for other regressors.

Beside the model, the other input into a regression analysis is some relevant sample data, consisting of the observed values of the dependent and explanatory variables for a sample of members of the ...

This example shows how to build a menu system that enables you to perform nonlinear regression from a menu. Six modules are stored on an IML storage disk. After you have stored them, use this example ...

Examination of the (sample) residuals resulting from the regression analysis can indicate failures of assumptions 1, 3, and 4. Such failures are not necessarily a bad thing: They can point the way to ...

This article outlines a general Bayesian approach to estimating a bivariate regression function in a nonparametric manner. It models the function using a bivariate regression spline basis with many ...

The discussion of the spherical regression model focuses on the interplay of the geometry of the plate boundaries and the statistical properties of a least square estimator. Because the errors in ...

Hilary Finucane, Brendan Bulik-Sullivan, Benjamin Neale, Alkes Price and colleagues introduce a new method, called stratified LD score regression, for partitioning heritability by functional ...