Since the equation of exponential smoothing method (ESM) is equivalent to (1,1) order ARMA model equation (or (0,1,1) order ARIMA model), new estimation method of smoothing constant in exponential smoothing method is proposed. Firstly, we make estimation of ARMA model parameter and then estimate smoothing constants. Thus we get theoretical solution by a simple way. New method is examined by applying to the sales data. Useful results are obtained. The score range of coefficient of autocorrelation function is limited for the solution. Therefore expanding the score range, extended ESM in which parameter varies expansively from the customary permitted range is examined and their handling method is proposed
Formerly, following method was proposed by us. Focusing that the equation of exponential smoothing m...
To predict the stock closing price, the method of the secondary exponential smoothing model (SESM) i...
This paper examines exponential smoothing constants that minimize summary error measures associated ...
Abstract. Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent...
Abstract—In industries, how to improve forecasting accuracy such as sales, shipping is an important ...
Abstract. Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent...
Abstract – Higher accurate forecasting in such fields as sales, shipping is an urgent necessity in i...
In industries, how to improve forecasting accuracy such as sales, shipping is an important issue. Th...
Given that the equation of the exponential smoothing method (ESM) is equivalent to the (1,1) order A...
Formerly, following method was proposed by us. Focusing that the equation of exponential smoothing m...
In this work the several exponential smoothing type methods are briefly described, which are often u...
The focus of this paper is on the relationship between the exponential smoothing methods of forecast...
An approach to exponential smoothing that relies on a linear single source of error state space mode...
summary:The paper deals with extensions of exponential smoothing type methods for univariate time se...
Adaptive exponential smoothing methods allow a smoothing parameter to change over time, in order to ...
Formerly, following method was proposed by us. Focusing that the equation of exponential smoothing m...
To predict the stock closing price, the method of the secondary exponential smoothing model (SESM) i...
This paper examines exponential smoothing constants that minimize summary error measures associated ...
Abstract. Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent...
Abstract—In industries, how to improve forecasting accuracy such as sales, shipping is an important ...
Abstract. Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent...
Abstract – Higher accurate forecasting in such fields as sales, shipping is an urgent necessity in i...
In industries, how to improve forecasting accuracy such as sales, shipping is an important issue. Th...
Given that the equation of the exponential smoothing method (ESM) is equivalent to the (1,1) order A...
Formerly, following method was proposed by us. Focusing that the equation of exponential smoothing m...
In this work the several exponential smoothing type methods are briefly described, which are often u...
The focus of this paper is on the relationship between the exponential smoothing methods of forecast...
An approach to exponential smoothing that relies on a linear single source of error state space mode...
summary:The paper deals with extensions of exponential smoothing type methods for univariate time se...
Adaptive exponential smoothing methods allow a smoothing parameter to change over time, in order to ...
Formerly, following method was proposed by us. Focusing that the equation of exponential smoothing m...
To predict the stock closing price, the method of the secondary exponential smoothing model (SESM) i...
This paper examines exponential smoothing constants that minimize summary error measures associated ...