The paper studies the seasonal time series as elements of a (finite dimensional) Hilbert space and proves that it is always better to consider a trend together with a seasonal component even the time series seams not to has one. We give a formula that determines the seasonal component in function of the considered trend that permits to compare the different kind of trends
summary:The paper suggests a generalization of widely used Holt-Winters smoothing and forecasting me...
This article proposes an alternative methodology for modeling and forecasting seasonal series. The a...
In this paper the focus is on two forecasting models for a monthly time series. The first model requ...
We present a method for investigating the evolution of trend and seasonality in an observed time ser...
We present a method for investigating the evolution of trend and seasonality in an observed time ser...
The traditional literature on seasonality has mainly focused attention on various statistical proced...
The decomposition of a given time series into trend, seasonal component, and irregular component is ...
The decomposition of a given time series into trend, seasonal component, and irregular component is ...
The decomposition of a given time series into trend, seasonal component, and irregular component is ...
The decomposition of a given time series into trend, seasonal component, and irregular component is ...
textabstractA recurring issue in modeling seasonal time series variables is the choice of the most a...
The decomposition of a given time series into trend, seasonal component, and irregular component is ...
New innovations state space modeling tools, incorporating Box-Cox transformations, Fourier series wi...
This chapter reviews the principal methods used by researchers when forecasting seasonal time series...
Summary. Unobserved components time series models decompose a time series into a trend, a season, a ...
summary:The paper suggests a generalization of widely used Holt-Winters smoothing and forecasting me...
This article proposes an alternative methodology for modeling and forecasting seasonal series. The a...
In this paper the focus is on two forecasting models for a monthly time series. The first model requ...
We present a method for investigating the evolution of trend and seasonality in an observed time ser...
We present a method for investigating the evolution of trend and seasonality in an observed time ser...
The traditional literature on seasonality has mainly focused attention on various statistical proced...
The decomposition of a given time series into trend, seasonal component, and irregular component is ...
The decomposition of a given time series into trend, seasonal component, and irregular component is ...
The decomposition of a given time series into trend, seasonal component, and irregular component is ...
The decomposition of a given time series into trend, seasonal component, and irregular component is ...
textabstractA recurring issue in modeling seasonal time series variables is the choice of the most a...
The decomposition of a given time series into trend, seasonal component, and irregular component is ...
New innovations state space modeling tools, incorporating Box-Cox transformations, Fourier series wi...
This chapter reviews the principal methods used by researchers when forecasting seasonal time series...
Summary. Unobserved components time series models decompose a time series into a trend, a season, a ...
summary:The paper suggests a generalization of widely used Holt-Winters smoothing and forecasting me...
This article proposes an alternative methodology for modeling and forecasting seasonal series. The a...
In this paper the focus is on two forecasting models for a monthly time series. The first model requ...