Forecasting with model averaging

Mixture of experts, ensembles and time series

May 4, 2022 — May 4, 2022

dynamical systems

ensemble

model selection

regression

signal processing

statistics

stochastic processes

time series

Time series prediction niceties, specialising on ensemble/model mixing methods. See also statistical learning theory for dependent data.

1 References

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Bousquet, and Warmuth. 2001. “Tracking a Small Set of Experts by Mixing Past Posteriors.” In Computational Learning Theory. Lecture Notes in Computer Science.

Carvalho, and Tanner. 2006. “Modeling Nonlinearities with Mixtures-of-Experts of Time Series Models.” International Journal of Mathematics and Mathematical Sciences.

Chen, and Liu. 2000. “Mixture Kalman Filters.” Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Davis, and Nielsen. 2020. “Modeling of Time Series Using Random Forests: Theoretical Developments.” Electronic Journal of Statistics.

Feng, Xu, and Mannor. 2017. “Outlier Robust Online Learning.” arXiv:1701.00251 [Cs, Stat].

Frühwirth-Schnatter. 2006. Finite Mixture and Markov Switching Models. Springer Series in Statistics.

Frühwirth-Schnatter, and Pamminger. 2010. “Model-Based Clustering of Categorical Time Series.” Bayesian Analysis.

———. n.d. “Bayesian Clustering of Categorical Time Series Using Finite Mixtures of Markov Chain Models.”

Huerta, Jiang, and Tanner. 2001. “Discussion: Mixtures of Time Series Models.” Journal of Computational and Graphical Statistics.

———. 2003. “Time Series Modeling Via Hierarchical Mixtures.” Statistica Sinica.

Jacobs. 2011. “Adapting to Non-Stationarity with Growing Predictor Ensembles.”

Kuznetsov, and Mohri. 2014. “Forecasting Non-Stationary Time Series: From Theory to Algorithms.”

Montgomery, Hollenbach, and Ward. n.d. “Improving Predictions Using Ensemble Bayesian Model Averaging.” Political Analysis.

Phillips. 1987. “Composite Forecasting: An Integrated Approach and Optimality Reconsidered.” Journal of Business & Economic Statistics.

Prado, Ferreira, and West. 2021. Time series: modeling, computation, and inference. Texts in statistical science.

West. 1993. “Mixture Models, Monte Carlo, Bayesian Updating and Dynamic Models.”

Wood, Rosen, and Kohn. 2011. “Bayesian Mixtures of Autoregressive Models.” Journal of Computational and Graphical Statistics.

Zeevi, Assaf J., Meir, and Adler. 1996. “Time Series Prediction Using Mixtures of Experts.” In Proceedings of the 9th International Conference on Neural Information Processing Systems. NIPS’96.

Zeevi, Assaf, Meir, and Adler. 1999. “Non-Linear Models for Time Series Using Mixtures of Autoregressive Models.”