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 ...

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

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.