Taking some form of moving averages yields a smoothing of time series which is delayed. However, taking moving averages in the reverse time direction gives a smoothing which is in advance. The two resulting smoothed time series are pointwise averaged getting as result a smoothed version with "no delay"
An original method of calculating the weight factors for moving averaging is suggested The advantage...
This article is on time loss methods based on time series and includes the study of basic methods fo...
A new iterative smoothing method based on the extended Kalman filter is introduced to smooth noisy c...
Taking some form of moving averages yields a smoothing of time series which is delayed. However, tak...
summary:The paper deals with some practical problems connected with the classical exponential smooth...
When sample estimates are plotted in time series, part of the irregularity displayed by the plotted ...
Both statistical and neural network methods may fail in forecasting time series even operating on a ...
A simple method for smoothing noisy data is to use a moving average. The original data is partitione...
In this paper, we present a unified theory of linear smoothing, which looks at the problem from a ti...
A Monte-Carlo weighted moving average procedure was developed for smoothing time series data. The ap...
Abstract. Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent...
A new NARMA based smoothing algorithm is introduced for chaotic and non-chaotic time series. The new...
Most of the data obtained by statistical agencies have to be adjusted, corrected or somehow processe...
Abstract. Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent...
Why the damped trend works The damped trend method of exponential smoothing is a benchmark that has ...
An original method of calculating the weight factors for moving averaging is suggested The advantage...
This article is on time loss methods based on time series and includes the study of basic methods fo...
A new iterative smoothing method based on the extended Kalman filter is introduced to smooth noisy c...
Taking some form of moving averages yields a smoothing of time series which is delayed. However, tak...
summary:The paper deals with some practical problems connected with the classical exponential smooth...
When sample estimates are plotted in time series, part of the irregularity displayed by the plotted ...
Both statistical and neural network methods may fail in forecasting time series even operating on a ...
A simple method for smoothing noisy data is to use a moving average. The original data is partitione...
In this paper, we present a unified theory of linear smoothing, which looks at the problem from a ti...
A Monte-Carlo weighted moving average procedure was developed for smoothing time series data. The ap...
Abstract. Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent...
A new NARMA based smoothing algorithm is introduced for chaotic and non-chaotic time series. The new...
Most of the data obtained by statistical agencies have to be adjusted, corrected or somehow processe...
Abstract. Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent...
Why the damped trend works The damped trend method of exponential smoothing is a benchmark that has ...
An original method of calculating the weight factors for moving averaging is suggested The advantage...
This article is on time loss methods based on time series and includes the study of basic methods fo...
A new iterative smoothing method based on the extended Kalman filter is introduced to smooth noisy c...
DOI
Add to ORKG