(2000). Bayesian dynamic factor models and portfolio allocation. Journal of Business and Economic Statistics 18:338-357.Aguilar O, West M. 2000. Bayesian dynamic factor model and portfolio allocation. Journal of Business and Economic Statistics, 18(3), 338-357....
Owyang, "Specifica- tion and Estimation of Bayesian Dynamic Factor Models: A Monte Carlo Analysis with an Application to Global House Price Comovement," in Eric Hillebrand and Siem Jan Koop- man, eds., Advances in Econometrics, Vol. 35, United Kingdom: Emerald Insight, 2015, chapter 15, ...
Robust sequential online prediction with dynamic ensemble of multiple models: A review 2.1 Bayesian Model Averaging In traditional statistical modeling, a stochastic model M is initially specified to represent a hypothesis on how data are generated. With M possessing a fixed structure, the corresponding...
2013. Bayesian Estimation of Sparse Dynamic Factor Models with Order- Independent Identification. Working paper, Studienzentrum Gerzensee.Kaufmann, S. and Schumacher, C.: 2013, Bayesian estimation of sparse dynamic factor model with order-... S Kaufmann,C Schumacher - Swiss National Bank, Study Cen...
► We present a Bayesian inference-based dynamic model to predict freeway travel times. ► The method provides the distribution of predicted travel times and their confidence intervals. ► We embed the model into an adaptive system to self-tune system evolution noise levels. ► The method...
Static and dynamic forecasts Stability analysis using eigenvalues Save your MCMC and estimation results for future use Factor variables Automatically create indicators based on categorical variables Form interactions among discrete and continuous variables ...
Time series generated by complex systems like financial markets and the earth’s atmosphere often represent superstatistical random walks: on short time scales, the data follow a simple low-level model, but the model parameters are not constant and can f
Keywords:Bayesianmethod;dynamiclinearmodel;bridgeresistance;adiscountfactor;Bayesianprediction 桥梁结构退化抗力预测的研究是桥梁结构时变可 靠度研究的关键问题。在结构性能的预测方法方面, 已经取得了不少的研究成果 [1‐3] ,如Asaoka法、时间 序列法、灰色预测法及神经网络法等。这些方法运用 ...
dynamicis the component for modeling dynamically changing predictors, which acceptsfeaturesas its argument. The above code plots the fitted result (top left). The one-day ahead prediction looks much better than the simple model, particularly around the crisis peak. The mean prediction error is0.099...
path integration bias Bayesian model leaky integration virtual reality optic flow-based navigation Introduction The world is inherently noisy and dynamic. To act successfully, we must continuously monitor our sensory inputs, gather evidence in favor of potential actions, and make subjectively good decisio...