GitHub

Implementing Generalized Ordered Logit Model with Non-Parallel Lines

I am currently working on a project that involves modeling ordinal outcomes where the proportional odds (parallel lines) assumption does not hold. Specifically, I need to fit a generalized ordered ...
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 ...
Scientific Research Publishing

Estimating the Likelihood of Cancer Occurrence Based on Patient Data and Lifestyle Factors: A Comparison between Logit and Probit Regression ()

1 Department of Statistics, Ladoke Akintola University of Technology, Ogbomoso, Nigeria. 2 Department of Statistics, Federal University of Technology Akure, Nigeria. 3 Department of Statistics, ...
GitHub

Bayesian spatial logit model

Oyama, Y., Murakami, D., Krueger, R. (2024) A hierarchical Bayesian logit model for spatial multivariate choice data. Journal of Choice Modelling 52: 100503. If you find this code useful, please cite ...
IEEE

Personalized Travel Recommendations Based on Asynchronous and Privacy-Preserving Mixed Logit Model

Abstract: A data-secure and cost-efficient Personalized Travel Recommendation (PTR) is necessary to develop urban intelligence in transportation. Although prevalent machine learning-based methods have ...
IEEE

Dynamic Recursive Logit Model for Vehicle Driving Route Choices and Path Inference With Incomplete Fixed Location Sensor Data

Abstract: This paper studies the estimation of dynamic route choice behavior of drivers with incomplete fixed location-based sensor data, such as radio frequency identification (RFID) data. Unlike ...