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 ...

We develop maximum likelihood estimation of logistic regression coefficients for a hybrid two-phase, outcome-dependent sampling design. An algorithm is given for determining the estimates by repeated ...

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 ...

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

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