JSTOR Daily

A modern maximum-likelihood theory for high-dimensional logistic regression

This is a preview. Log in through your library . Abstract Students in statistics or data science usually learn early on that when the sample size n is large relative to the number of variables p, ...
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 ...
Simon Fraser University

Comparison of CATMOD, GENMOD, LOGISTIC, and PROBIT Procedures

The LOGISTIC, GENMOD, PROBIT, and CATMOD procedures can all be used for statistical modeling of categorical data. The CATMOD procedure provides maximum likelihood estimation for logistic regression, ...
Nature

Logistic regression

In recent columns we showed how linear regression can be used to predict a continuous dependent variable given other independent variables 1,2. When the dependent variable is categorical, a common ...
Simon Fraser University

Existence of Maximum Likelihood Estimates

The likelihood equation for a logistic regression model does not always have a finite solution. Sometimes there is a nonunique maximum on the boundary of the parameter space, at infinity. The ...
Risk

Smoothing algorithms by constrained maximum likelihood: methodologies and implementations for Comprehensive Capital Analysis and Review stress testing and International ...

In the process of loan pricing, stress testing, capital allocation, modeling of probability of default (PD) term structure and International Financial Reporting Standard 9 expected credit loss ...