summary:The paper suggests a generalization of widely used Holt-Winters smoothing and forecasting method for seasonal time series. The general concept of seasonality modeling is introduced both for the additive and multiplicative case. Several special cases are discussed, including a linear interpolation of seasonal indices and a usage of trigonometric functions. Both methods are fully applicable for time series with irregularly observed data (just the special case of missing observations was covered up to now). Moreover, they sometimes outperform the classical Holt-Winters method even for regular time series. A simulation study and real data examples compare the suggested methods with the classical one
The Holt-Winters method is a well-known forecasting method used in time-series analysis to forecast ...
A new approach to forecasting seasonal data is proposed where seasonal terms can be updated using th...
This chapter reviews the principal methods used by researchers when forecasting seasonal time series...
summary:The paper suggests a generalization of widely used Holt-Winters smoothing and forecasting me...
Title: Methods for periodic and irregular time series Author: Mgr. Tomáš Hanzák Department: Departme...
summary:Popular exponential smoothing methods dealt originally only with equally spaced observations...
This study deals with forecasting economic time series that have strong trends and seasonal patterns...
A method of adjusting for seasonality and trends is demonstrated using general merchanise retail dat...
Time series are one of the most common data types encountered by data scientists and, in the context...
Title: Holt-Winters method with missing observations and its actuarial application Author: Jiří Greg...
A new class of models for data showing trend and multiplicative seasonality is presented. The model...
Exponential smoothing methods are very commonly used for forecasting demand because they are simple,...
A parsimonious method of exponential smoothing is introduced for time series generated from a combin...
The Holt-Winters method is a well-known forecasting method used in time-series analysis to forecast ...
A new approach to forecasting seasonal data is proposed where seasonal terms can be updated using th...
This chapter reviews the principal methods used by researchers when forecasting seasonal time series...
summary:The paper suggests a generalization of widely used Holt-Winters smoothing and forecasting me...
Title: Methods for periodic and irregular time series Author: Mgr. Tomáš Hanzák Department: Departme...
summary:Popular exponential smoothing methods dealt originally only with equally spaced observations...
This study deals with forecasting economic time series that have strong trends and seasonal patterns...
A method of adjusting for seasonality and trends is demonstrated using general merchanise retail dat...
Time series are one of the most common data types encountered by data scientists and, in the context...
Title: Holt-Winters method with missing observations and its actuarial application Author: Jiří Greg...
A new class of models for data showing trend and multiplicative seasonality is presented. The model...
Exponential smoothing methods are very commonly used for forecasting demand because they are simple,...
A parsimonious method of exponential smoothing is introduced for time series generated from a combin...
The Holt-Winters method is a well-known forecasting method used in time-series analysis to forecast ...
A new approach to forecasting seasonal data is proposed where seasonal terms can be updated using th...
This chapter reviews the principal methods used by researchers when forecasting seasonal time series...