Bayesian Forecasting
نویسنده
چکیده
Bayesian Forecasting encompasses statistical theory and methods in time series analysis and time series forecasting, particularly approaches using dynamic and state space models, though the underlying concepts and theoretical foundation relate to probability modelling and inference more generally. This entry focuses speciically in the time series and dynamic modelling domain, with mention of related areas.
منابع مشابه
Comparison of Neural Network Models, Vector Auto Regression (VAR), Bayesian Vector-Autoregressive (BVAR), Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) Process and Time Series in Forecasting Inflation in Iran
This paper has two aims. The first is forecasting inflation in Iran using Macroeconomic variables data in Iran (Inflation rate, liquidity, GDP, prices of imported goods and exchange rates) , and the second is comparing the performance of forecasting vector auto regression (VAR), Bayesian Vector-Autoregressive (BVAR), GARCH, time series and neural network models by which Iran's inflation is for...
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متن کاملBayesian Forecasting
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