On the Prediction of a Nonstationary Exponential Distribution Based on Bayes Decision Theory

Daiki Koizumi

2023

Abstract

A prediction problem with a nonstationary exponential distribution based on the Bayes decision theory was considered in this paper. The proposed predictive algorithm is based on both posterior and predictive distributions in a Bayesian context. The predictive estimator satisfies the Bayes optimality, which guarantees a minimum average error rate with a nonstationary probability model, a squared loss function, and a prior distribution of parameter. Finally, the predictive performance of the proposed algorithm was evaluated via comparison with the stationary exponential distribution using real meteorological data.

Paper Citation

in Harvard Style

Koizumi D. (2023). On the Prediction of a Nonstationary Exponential Distribution Based on Bayes Decision Theory. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 193-201. DOI: 10.5220/0011632500003393

in Bibtex Style

@conference{icaart23,
author={Daiki Koizumi},
title={On the Prediction of a Nonstationary Exponential Distribution Based on Bayes Decision Theory},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={193-201},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011632500003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - On the Prediction of a Nonstationary Exponential Distribution Based on Bayes Decision Theory
SN - 978-989-758-623-1
AU - Koizumi D.
PY - 2023
SP - 193
EP - 201
DO - 10.5220/0011632500003393