Bayesian analysis offers a robust framework for deciphering the intricate dynamics of time series data. By treating unknown parameters as random variables, this approach incorporates prior information ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...

Learn to apply Bayes' theorem in financial forecasting for insightful, updated predictions. Enhance decision-making with ...

We develop methodology to bridge scenario analysis and risk forecasting, leveraging their respective strengths in policy settings. The methodology, rooted in Bayesian analysis, addresses the ...

Pantelis Samartsidis, Claudia R. Eickhoff, Simon B. Eickhoff, Tor D. Wager, Lisa Feldman Barrett, Shir Atzil, Timothy D. Johnson, Thomas E. Nichols Journal of the Royal Statistical Society. Series C ...

1. Difference Equations -- 2. Lag Operators -- 3. Stationary ARMA Processes -- 4. Forecasting -- 5. Maximum Likelihood Estimation -- 6. Spectral Analysis -- 7. Asymptotic Distribution Theory -- 8.