JSTOR Daily

JOINT CONDITIONAL LIKELIHOOD ESTIMATOR IN LOGISTIC REGRESSION WITH MISSING COVARIATE DATA

This is a preview. Log in through your library . Abstract This article considers semiparametric estimation in logistic regression with missing covariates. In a ...
JSTOR Daily

THE PHASE TRANSITION FOR THE EXISTENCE OF THE MAXIMUM LIKELIHOOD ESTIMATE IN HIGH-DIMENSIONAL LOGISTIC REGRESSION

This is a preview. Log in through your library . Abstract This paper rigorously establishes that the existence of the maximum likelihood estimate (MLE) in high-dimensional logistic regression models ...
technologynetworks

Logistic Regression

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...
Visual Studio Magazine

Logistic Regression Using PyTorch with L-BFGS

Dr. James McCaffrey of Microsoft Research demonstrates applying the L-BFGS optimization algorithm to the ML logistic regression technique for binary classification -- predicting one of two possible ...