Random coefficient state-space model: Estimation and performance in M3–M4 competitions-Reference-Cited by-同舟云学术

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Random coefficient state-space model: Estimation and performance in M3–M4 competitions

Published:2022-01 Issue:1 Volume:38 Page:352-366
ISSN:0169-2070
Container-title:International Journal of Forecasting
language:en
Short-container-title:International Journal of Forecasting

Author:

Sbrana Giacomo,Silvestrini Andrea

Publisher

Elsevier BV

Subject

Business and International Management

Reference34 articles.

1. A model confidence set approach to the combination of multivariate volatility forecasts;Amendola;International Journal of Forecasting,2020

2. The theta model: a decomposition approach to forecasting;Assimakopoulos;International Journal of Forecasting,2000

3. The model confidence set package for R;Bernardi;International Journal of Computational Economics and Econometrics,2018

4. Smoothing, forecasting and prediction of discrete time series;Brown,1963

5. Comparing predictive accuracy;Diebold;Journal of Business & Economic Statistics,1995

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1. Comparative Analysis of Deep Learning Models for Silver Price Prediction: CNN, LSTM, GRU and Hybrid Approach;Akdeniz Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi;2024-02-08

2. A Two-Step Estimation Method for a Time-Varying INAR Model;Axioms;2023-12-27

3. The RWDAR model: A novel state-space approach to forecasting;International Journal of Forecasting;2023-04

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