TEMPORAL AGGREGATION OF STATIONARY AND NONSTATIONARY DISCRETE-TIME PROCESSES By Henghsiu Tsai and K. S. Chan
نویسندگان
چکیده
We study the autocorrelation structure and the spectral density function of aggregates from a discrete-time process. The underlying discrete-time process is assumed to be a stationary AutoRegressive Fractionally Integrated Moving-Average (ARFIMA) process, after suitable number of differencing if necessary. We derive closed-form expressions for the limiting autocorrelation function and the normalized spectral density of the aggregates, as the extent of aggregation increases to infinity. These results are then used to assess the loss of forecasting efficiency due to aggregation.
منابع مشابه
Temporal aggregation of stationary and nonstationary discrete-time processes
We study the autocorrelation structure and the spectral density function of aggregates from a discrete-time process. The underlying discrete-time process is assumed to be a stationary AutoRegressive Fractionally Integrated MovingAverage (ARFIMA) process, after suitable number of differencing if necessary. We derive closed-form expressions for the limiting autocorrelation function and the normal...
متن کاملSome New Methods for Prediction of Time Series by Wavelets
Extended Abstract. Forecasting is one of the most important purposes of time series analysis. For many years, classical methods were used for this aim. But these methods do not give good performance results for real time series due to non-linearity and non-stationarity of these data sets. On one hand, most of real world time series data display a time-varying second order structure. On th...
متن کاملThe Stationary - NonStationary Process and The Variable Roots Difference Equations
Stochastic, processes can be stationary or nonstationary. They depend on the magnitude of shocks. In other words, in an auto regressive model of order one, the estimated coefficient is not constant. Another finding of this paper is the relation between estimated coefficients and residuals. We also develop a catastrophe and chaos theory for change of roots from stationary to a nonstationary one ...
متن کاملEffect of Temporal Aggregation on Persistence and Integration
The impulse response function and related persistence measures are discussed for fractionally integrated processes, where the order of integration also covers the nonstationary case. Then we obtain a general result that characterizes the effect of temporal aggregation in the frequency domain for arbitrary stationary processes. Temporal aggregation includes here cumulation of flow variables as w...
متن کاملA test for stationarity for spatio-temporal data
Many random phenomena in the environmental and geophysical sciences are functions of both space and time; these are usually called spatio-temporal processes. Typically, the spatio-temporal process is observed over discrete equidistant time and at irregularly spaced locations in space. One important aim is to develop statistical models based on what is observed. While doing so a commonly used as...
متن کامل