Multivariate exponential smoothing: a Bayesian forecast approach based on simulation

DOI10.1016/j.matcom.2008.09.004zbMath1163.62072OpenAlexW2045393325MaRDI QIDQ1005220

Ana Corberán-Vallet, Enriqueta Vercher, José D. Bermúdez

Publication date: 9 March 2009

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.matcom.2008.09.004

zbMATH Keywords

Monte Carlo methodsmultivariate time seriesBayesian forecastingHolt-Winters modelvariate generation

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15) Monte Carlo methods (65C05)

Related Items (1)

Holt–Winters model with grey generating operator and its application

Uses Software

• LBFGS-B

Cites Work

• Unnamed Item
• Handbook of economic forecasting. Volume 1
• A decision support system methodology for forecasting of time series based on soft computing
• Bayesian forecasting and dynamic models
• ESTIMATION AND TESTING OF A MULTIVARIATE EXPONENTIAL SMOOTHING MODEL
• Improving demand forecasting accuracy using nonlinear programming software
• Analysis and Generalisation of a Multivariate Exponential Smoothing Model
• Forecasting Applications of an Adaptive Multiple Exponential Smoothing Model
• Estimation and Prediction for a Class of Dynamic Nonlinear Statistical Models
• Applied Multivariate Analysis
• A Limited Memory Algorithm for Bound Constrained Optimization
• Holt–Winters Forecasting: An Alternative Formulation Applied to UK Air Passenger Data
• An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias

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