Exponential smoothing methods are the most used in time series modeling and forecasting, due to their versatility and the vast model option they integrate. Also, within the computing statistical area, Bootstrap methodology is widely applied in statistical inference concerning time series. Therefore, this study’s main objective is to analyse Holt-Winters exponential smoothing method’s performance associated to Bootstrap methodology, as an alternative procedure for modeling and forecasting in time series. The Bootstrap methodology combined with Holt-Winters methodology is applied to a study case on an environmental time series concerning a surface water quality variable, Dissolved Oxygen (DO). The proposed procedure allows to obtaining better...
summary:Popular exponential smoothing methods dealt originally only with equally spaced observations...
Exponential smoothing methods are very commonly used for forecasting demand because they are simple,...
Forecasting in time series is one of the main purposes for applying time series models. The choice o...
Publicado em "AIP Conference Proceedings", Vol. 1648Exponential smoothing methods are the most used...
This study deals with forecasting economic time series that have strong trends and seasonal patterns...
Abstract: Robust versions of the exponential and Holt-Winters smoothing method for forecasting are p...
Exponential smoothing methods are one of the classical time series forecasting methods. It is well k...
Robust versions of the exponential and Holt-Winters smoothing method for forecasting are presented. ...
Robust versions of the exponential and Holt–Winters smoothing method for forecasting are presented. ...
summary:The paper suggests a generalization of widely used Holt-Winters smoothing and forecasting me...
Robust versions of the exponential and Holt–Winters smoothing method for forecasting are presented. ...
In this work, are developed an experimental computer program in Matlab language version 7.1 from the...
A Research Report submitted to the Faculty of Science in partial fulfilment of the requirements for...
The core proposition behind this research is to create innovative methods of bootstrapping that can ...
Dissertação de mestrado em EstatísticaUma série temporal é um conjunto de observações ordenadas no t...
summary:Popular exponential smoothing methods dealt originally only with equally spaced observations...
Exponential smoothing methods are very commonly used for forecasting demand because they are simple,...
Forecasting in time series is one of the main purposes for applying time series models. The choice o...
Publicado em "AIP Conference Proceedings", Vol. 1648Exponential smoothing methods are the most used...
This study deals with forecasting economic time series that have strong trends and seasonal patterns...
Abstract: Robust versions of the exponential and Holt-Winters smoothing method for forecasting are p...
Exponential smoothing methods are one of the classical time series forecasting methods. It is well k...
Robust versions of the exponential and Holt-Winters smoothing method for forecasting are presented. ...
Robust versions of the exponential and Holt–Winters smoothing method for forecasting are presented. ...
summary:The paper suggests a generalization of widely used Holt-Winters smoothing and forecasting me...
Robust versions of the exponential and Holt–Winters smoothing method for forecasting are presented. ...
In this work, are developed an experimental computer program in Matlab language version 7.1 from the...
A Research Report submitted to the Faculty of Science in partial fulfilment of the requirements for...
The core proposition behind this research is to create innovative methods of bootstrapping that can ...
Dissertação de mestrado em EstatísticaUma série temporal é um conjunto de observações ordenadas no t...
summary:Popular exponential smoothing methods dealt originally only with equally spaced observations...
Exponential smoothing methods are very commonly used for forecasting demand because they are simple,...
Forecasting in time series is one of the main purposes for applying time series models. The choice o...