Robust exponential smoothing of multivariate time series

A new adaptive exponential smoothing method for non-stationary time series with level shifts

Simple exponential smoothing (SES) methods are the most commonly used methods in forecasting and time series analysis. However, they are generally insensitive to non-stationary structural events such as level shifts, ramp shifts, and spikes or impulses. Similar to that of outliers in stationary time series, these non-stationary events will lead to increased level of errors in the forecasting pr...

A Comparison Between Time Series, Exponential Smoothing, and Neural Network Methods To Forecast GDP of Iran

Prediction of global sea cucumber capture production based on the exponential smoothing and ARIMA models

Sea cucumber catch has followed “boom-and-bust” patterns over the period of 60 years from 1950-2010, and sea cucumber fisheries have had important ecological, economic and societal roles. However, sea cucumber fisheries have not been explored systematically, especially in terms of catch change trends. Sea cucumbers are relatively sedentary species. An attempt was made to explore whether the tim...

Prediction of global sea cucumber capture production based on the exponential smoothing and ARIMA models

Sea cucumber catch has followed “boom-and-bust” patterns over the period of 60 years from 1950-2010, and sea cucumber fisheries have had important ecological, economic and societal roles. However, sea cucumber fisheries have not been explored systematically, especially in terms of catch change trends. Sea cucumbers are relatively sedentary species. An attempt was made to explore whe...

Multivariate exponential smoothing for forecasting tourist arrivals to Australia and New Zealand

In this paper we propose a new set of multivariate stochastic models that capture time varying seasonality within the vector innovations structural time series (VISTS) framework. These models encapsulate exponential smoothing methods in a multivariate setting. The models considered are the local level, local trend and damped trend VISTS models with an additive multivariate seasonal component. W...