Abstract: This study examines logit models applied to the truck route choice problem using GPS trucking data from the Dallas metropolitan area. Instead of assuming a constant coefficient for each ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Abstract: This article presents a novel deep learning model, the Attentive Bayesian Multi-Stage Forecasting Network (ABMF-Net), designed for robust forecasting of electricity price (USD/MWh) and ...

This article explores the potential of large language models (LLMs) in reliability systems engineering, highlighting their ...

Confirming a non-universal X-ray-to-ultraviolet relation with cosmic time is quite surprising and challenges our ...

🕹️ Try and Play with VAR! We provide a demo website for you to play with VAR models and generate images interactively. Enjoy the fun of visual autoregressive modeling! We provide a demo website for ...

This study examined the relationship between the Monetary Policy Rate (MPR) and inflation across five continents from 2014 to 2023 using both Frequentist and Bayesian Linear Mixed Models (LMM). It ...

A study conducted by experts from the University of the Philippines-Diliman showed that logistic regression is a reliable ...

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...

Four billion years ago, Earth was violent, hot, and unstable. Yet new research suggests that by then, life had already ...