ABSTRACT: Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the vehicle crash severity as it does not require the assumption of normality, linearity, or ...

TStat’s introduction to micro data analysis course focuses, from both a theoretical and applied point of view, on the following methodologies: count models, binary dependent variable models, ...

This project explores the determinants of inflation prediction errors using data from the Survey of Consumer Expectations (SCE) from 2013 to 2023 and monthly National and yearly State-level PCE. The ...

Abstract: Multinomial logistic regression provides the standard penalised maximumlikelihood solution to multi-class pattern recognition problems. More recently, the development of sparse multinomial ...

A generic random effects formulation for the Dirichlet negative multinomial distribution is developed together with a convenient regression parameterization. A ...

It is essential in a standard linear regression analysis that dependent variables are continuous. However, using the standard linear regression for the analysis of a double-level or multi-level ...