Stationary And Non-Stationary Time Series
AbstractThe paper „Stationary and Non-stationary Time Series” presents in a theoretical approach, the concept of time series, its characteristics which are: variability, homogeneity, periodicity and interdependence of time series terms, from which result the methods of estimation and analysis of time series, specific for each component (trend, periodical component-cyclical or seasonal, random component). As time series terms have or havn’t an evolution in time, it is stationary and non-stationary. In the case of stationary time series in the paper are defined the white-noise processes and the autoregressive processes. Since most processes are non-stationary by transformations we obtain stationary time series and in the paper are presented the restrictions for which an autoregresive process of moving average is stationary. In the paper are approached also non-stationary processes by deterministic type and by stochastic type as the way to achieve stationary which mean the trend estimation and its elimination from the initial time series.
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Bibliographic InfoArticle provided by "Stefan cel Mare" University of Suceava, Romania, Faculty of Economics and Public Administration in its journal The Annals of the "Stefan cel Mare" University of Suceava. Fascicle of The Faculty of Economics and Public Administration.
Volume (Year): 10 (2010)
Issue (Month): 1(11) (June)
stationary time series; non-stationary time series; white-noise process; autoregressive moving average process; autocorrelation function.;
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