A research team introduces a hierarchical Bayesian spatial approach that integrates UAV and terrestrial LiDAR data to estimate AGB of individual trees in natural secondary forests of northeastern ...

What’s often misunderstood about Google’s incrementality testing and how Bayesian models use probability to guide better ...

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 ...

This important study reports three experiments examining how the subjective experience of task regularities influences perceptual decision-making. Although the evidence linking subjective ratings to ...

After a period of sharp deceleration, inflation in Croatia has inched up since late 2024 to about 4–4½ percent year-on-year ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

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

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

Bayesian inference is a statistical method of inductive reasoning based on the reassessment of competing hypotheses in the presence of new evidence. Conceptually similar to the scientific method ...

Access to blood transfusions emerged as the most highly valued service, with a mean standardised importance score of 20.53.

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 ...

Researchers explain how nitrate from farming and fish ponds moves through water and pollutes freshwater lakes.