Tag Logistic regression

Sin categoría, Statistics

An epic dance

Multiple regression regularization (shrinkage) techniques can be very useful to address collinearity or overfitting problems. In addition, they can be used to select the independent variables and reduce multidimensionality, achieving more robust and easy-to-interpret models. Ridge, lasso and elastic network regression techniques are described.

Manuel Molina
12/05/2023

Sin categoría, Statistics

The paradox of the air

The parameters that report on the quality of a multiple logistic regression model and that are usually provided by the statistical programs with which they are carried out are reviewed. Emphasis is placed on the goodness of fit, the predictive capacity and the statistical significance of the model.

Manuel Molina
09/25/2023

Sin categoría, Statistics

A simple relationship

Simple regression. The concept of regression is defined and the most used simple regression models are detailed: linear, logistic and proportional hazards regression.

Manuel Molina
05/31/2016