BIOENGINEER

New Methods Tame Bayesian Inference When Prior Covariances Lose Rank

Researchers have introduced new dimension and model reduction methods that extend optimal Bayesian inference to problems with ...
GlobalSpec

Chapter 7: Bayesian Forecasting of Options Prices A Natural Framework for Pooling Historical and Implied Volatility Information

Bayesian statistical methods are naturally oriented towards pooling, in a rigorous way, information coming from separate sources. It has been suggested that both historical and implied volatilities ...
ilo.org

Forecasting Labour Market Outcomes Using Bayesian Hierarchical Panel VARs

This webinar explores how advanced Bayesian forecasting models can improve predictions of labour market trends and support more informed policy decisions. Bayesian methods are being increasingly used ...

ExaRing+: Bayesian Part 2—When Small Evidence Changes Judgments

Probabilities that created rebels, hidden signatures, unrecorded drivers, inbox gatekeepers, and those who predict the ...
JSTOR Daily

Vol. 26, No. 4, October 2016, Bayesian Inference, Environment Statistics, Time Series Analysis, and Their Applications

BAYESIAN FORECASTING OF DEMOGRAPHIC RATES FOR SMALL AREAS: EMIGRATION RATES BY AGE, SEX, AND REGION IN NEW ZEALAND, 2014-2038 BAYESIAN FORECASTING OF DEMOGRAPHIC RATES FOR SMALL AREAS: EMIGRATION ...
CU Boulder News & Events

Bayesian Hierarchical Network Model for Forecasting Daily River Stage in a River Network

A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...