A state space framework for automatic forecasting using exponential smoothing methods
نویسندگان
چکیده
منابع مشابه
A state space framework for automatic forecasting using exponential smoothing methods
We provide a new approach to automatic forecasting based on an extended range of exponential smoothing methods. Each method in our taxonomy of exponential smoothing methods provides forecasts that are equivalent to forecasts from a state space model. This equivalence allows: (1) easy calculation of the likelihood, the AIC and other model selection criteria; (2) computation of prediction interva...
متن کاملAutomatic forecasting with a modified exponential smoothing state space framework
A new automatic forecasting procedure is proposed based on a recent exponential smoothing framework which incorporates a Box-Cox transformation and ARMA residual corrections. The procedure is complete with well-defined methods for initialization, estimation, likelihood evaluation, and analytical derivation of point and interval predictions under a Gaussian error assumption. The algorithm is exa...
متن کاملForecasting based on state space models for exponential smoothing
In business, there is a frequent need for fully automatic forecasting that takes into account trend, seasonality and other features of the data without need for human intervention. In supply chain management, for example, forecasts of demand are required on a regular basis for very large numbers of time series, so that inventory levels can be planned to provide an acceptable level of service to...
متن کاملForecasting with exponential smoothing methods and bootstrap
The Boot.EXPOS procedure is an algorithm that combines the use of exponential smoothing methods with the bootstrap methodology for obtaining forecasts. In previous works the authors have studied and analyzed the interaction between these two methodologies. The initial sketch of the procedure was developed, modified and evaluated until its final form designated as Boot.EXPOS.
متن کاملShort-term Solar Irradiance Forecasting Using Exponential Smoothing State Space Model
We forecast high resolution solar irradiance time series using an exponential smoothing state space (ESSS) model. To stationarize the irradiance data before applying linear time series models, we propose a novel Fourier trend model and compare the performance with other popular trend models using residual analysis and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) stationarity test. Using the opt...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Forecasting
سال: 2002
ISSN: 0169-2070
DOI: 10.1016/s0169-2070(01)00110-8