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Forecasting simultaneously high-dimensional time series : a robust model-based clustering approach

Wang, Yongning; Tsay, Ruey S.; Ledolter, Johannes; … - In: Journal of forecasting 32 (2013) 8, pp. 673-684

Persistent link: https://www.econbiz.de/10010344465

Factor analysis regression for predictive modeling with high-dimensional data

Carter, Randy L.; Michael, Netsanet - In: Journal of quantitative economics 20 (2022), pp. 115-132

Persistent link: https://www.econbiz.de/10013441609

A comparison of neural networks and Bayesian MCMC for the Heston model estimation (forget statistics – machine learning is sufficient!)

Witzany, Jiří; Fičura, Milan - 2023

Persistent link: https://www.econbiz.de/10014338462

Inference using simulated neural moments

Creel, Michael D. - In: Econometrics : open access journal 9 (2021) 4, pp. 1-15

This paper studies method of simulated moments (MSM) estimators that are implemented using Bayesian methods, specifically Markov chain Monte Carlo (MCMC). Motivation and theory for the methods is provided by Chernozhukov and Hong (2003). The paper shows, experimentally, that confidence intervals...

Persistent link: https://www.econbiz.de/10012642418

Inference using simulated neural moments

Creel, Michael D. - 2020 - This version: November 2020

Persistent link: https://www.econbiz.de/10012431141

NNPF : Neural Network Particle Filter for time series data

Peerlings, Dewi; Brakel, Jan A. van den; Baştürk, Nalan - 2024

Persistent link: https://www.econbiz.de/10014524761

On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank : an application of flexible sampling methods using neural networks

Hoogerheide, Lennart F. (contributor); … - 2005

Persistent link: https://www.econbiz.de/10002823287

On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank : an application of flexible sampling methods using neural networks

Hoogerheide, Lennart F. (contributor); … - 2005

Persistent link: https://www.econbiz.de/10003287623

On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank : an application of flexible sampling methods using neural networks

Hoogerheide, Lennart F.; Kaashoek, Johan F.; Dijk, … - In: Journal of econometrics 139 (2007) 1, pp. 154-180

Persistent link: https://www.econbiz.de/10003516747

On the Shape of Posterior Densities and Credible Sets in Instrumental Variable Regression Models with Reduced Rank : An Application of Flexible Sampling Methods Using Neural Networks

Hoogerheide, Lennart F. - 2006

Likelihoods and posteriors of instrumental variable regression models with strong endogeneity and/or weak instruments may exhibit rather non-elliptical contours in the parameter space. This may seriously affect inference based on Bayesian credible sets. When approximating such contours using...

Persistent link: https://www.econbiz.de/10012734627