To avoid these, penalized maximum likelihood estimates are introduced, which give estimates of the logistic parameters and a nonparametric spline estimate of the marginal distribution of x. Extensions ...

Norman E. Breslow, Richard Holubkov, Maximum Likelihood Estimation of Logistic Regression Parameters Under Two- Phase, Outcome-Dependent Sampling, Journal of the Royal Statistical Society.

The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity.

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you ...

As the title “Practical Regression” suggests, these notes are a guide to performing regression in practice.This technical note discusses maximum likelihood estimation (MLE). The note explains the ...

Regression can be used on categorical responses to estimate probabilities and to classify.