The paper deals with extensions of exponential smoothing type methods for univariate time series with irregular observations. An alternative method to Wright’s modification of simple exponential smoothing based on the corresponding ARIMA process is suggested. Exponential smoothing of order m for irregular data is derived. A similar method using a DLS (discounted least squares) estimation of pol...

The main objective of this paper is to provide analytical expressions for forecast variances that can be used in prediction intervals for the exponential smoothing methods. These expressions are based on state space models with a single source of error that underlie the exponential smoothing methods. Three general classes of the state space models are presented. The first class is the standard ...

In this article we discuss invertibility conditions for some state space models, including the models that underly simple exponential smoothing, Holt’s linear method, Holt-Winters’ additive method and damped trend versions of Holt’s and Holt-Winters’ methods. The parameter space for which the model is invertible is compared to the usual parameter regions. We find that the usual parameter restri...

conclusions addressing and removing explainable patterns of syndromic data on meningitis is necessary to timely and accurately detection of meningitis epidemics. it was concluded that decomposition methods had better performance compared to the model based ones. background meningitis is one of the most disturbing infectious diseases due to mortality, morbidity and its ability to cause epidemic....

Exponential smoothing methods gave poor forecast accuracy in Fildes et al.’s study of telecommunications time series. We reexamine this study and show that parameter optimization improves the accuracy of the Holt and damped trend methods. Further improvement occurs when the time series are trimmed to eliminate irrelevant early data, and when the methods are fitted to minimize the MAD rather tha...

This paper introduces five new univariate exponentially weighted methods for forecasting intraday time series that consist of both intraweek and intraday seasonal cycles. Applications of relevance include forecasting volumes of call centre arrivals, transportation, e-mail traffic and electricity load. The first method that we develop extends an exponential smoothing formulation that has been us...

In this study, a hybrid synergy model integrating exponential smoothing and neural network is proposed for financial time series prediction. The proposed model attempts to incorporate the linear characteristics of an exponential smoothing model and nonlinear patterns of neural network to create a “synergetic” model via the linear programming technique. For verification, two real-world financial...

The importance of the measles immunization vaccine for children up to age 9 months prevent from getting sick with or reduce transmission rate in surrounding environment, especially at Gambir Health Center. This demand is still considered ineffective and there often an oversupply vaccines, which results a buildup vaccines storage. purpose this study was create needs forecasting system using Sing...