Maximum likelihood estimation of the parameters of the binary logistic regression model for $\pr (H\mid x)$ is discussed with separate discussion of sampling from (i) the conditional distribution of H ...

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 ...

Identify characteristics of “good” estimators and be able to compare competing estimators. Construct sound estimators using the techniques of maximum likelihood and method of moments estimation.

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