Bayesian spatial statistics and modeling represent a robust inferential framework where uncertainty in spatial processes is explicitly quantified through probability distributions. This approach ...

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 ...

Background Conventionally, frequentist approach has been used to model health state valuation data. Recently, researchers started to explore the use of Bayesian methods in this area. Objectives This ...

Here are 11 free NPTEL data science and analytics courses from leading IITs cover graph theory, Bayesian modelling, Python, R, databases and big-data stats. These are all free to audit, and enrolment ...

In traditional phase I and II clinical trial designs, toxicity and efficacy are often modelled as binary outcomes. Such methods ignore information on when the outcome event occurs, such as ...