Why marketing mix modeling is still hard to get right

Open-source tools have made MMM more accessible, but reliable results still depend on clean data, thoughtful modeling, and ...
IEEE

Interacting Large Language Model Agents. Bayesian Social Learning Based Interpretable Models

Abstract: This paper discusses the theory and algorithms for interacting large language model agents (LLMAs) using methods from statistical signal processing and microeconomics. While both fields are ...
ascopubs.org

Canine Olfaction Combined With Bayesian Modeling for Multicancer Detection From Breath ...

Circulating Tumor DNA Assessment of Disease Response in Large B-Cell Lymphoma: Lisocabtagene Maraleucel Versus Autologous Stem Cell Transplantation Standard Therapy We conducted an assessor-masked, ...
eLife

Hierarchical Bayesian modeling of multiregion brain cell count data

This study proposes an important new approach to analyzing cell-count data, which are often undersampled and cannot be accurately assessed using traditional statistical methods. The case studies ...
GitHub

SandyGCabanes/Anonymized-Survey-Data-Modeling-with-Bayesian-Networks-in-Python

Synthetic dataset outputs for public analysis without privacy risk. Part of my current workflow as survey leader of the Data Engineering Pilipinas group. Comparable distributions per column: based on ...
Hacker

Understanding Bayesian Networks: A Graphical Model for Uncertainty

Bayesian Network (BN) [15] is a probabilistic graphical model that represents a set of random variables and their conditional probabilities via a directed acyclic graph (DAG). In these graphical ...
pv magazine International

PVRadar launches Python programming tool to ease site-specific loss modeling

German software company PVRadar Labs has released a Python programming package for solar asset owners and engineers that want to build site-specific models. German software company PVRadar Labs has ...