Autoregressive Process

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Autoregressive Process

Any process or model that uses past data to predict future data. Technical analysis, for example, is an autoregressive process. See also: Forecasting.
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By taking into account time-lagged soil water content, time-lagged soil temperature, autoregressive processes and seasonality, the model provides more-detailed information on the nature of the relationship between [N.
This is the improved version of the Dickey-Fuller test since it accommodates higher-order autoregressive processes in [e.
Among the topics are gradient-based algorithms with applications to signal-recovery problems, graphical models of autoregressive processes, convex analysis for non-negative blind source separation with applications in imaging, robust broadband adaptive beamforming using convex optimization, and cooperative distributed multi- agent optimization.
Here, a is a diagonal matrix of elements in [0, 1) driving the stationary autoregressive processes.
Testing Cointegration in Infinite Order Vector Autoregressive Processes.
To examine the nature of various nonlinear estimates, we generated a large number of series from second-order autoregressive processes.
Model selection in partially nonstationary vector autoregressive processes with reduced rank structure.
A second approach is to build dynamics into the unobserved factors themselves by modeling them as autoregressive processes.
Estimation of the above relationship requires specification of the maximum number of lags, [Rho] and [Gamma] (or [Gamma]' and [Rho]' in reverse causality), for the autoregressive processes.
Some subjects covered include defect list compression, rate-distortion functions for nonstationary Gaussian autoregressive processes, high-resolution functional quantization, and word-based statistical compressors as natural language compression boosters.
1992c, "A Representation of Vector Autoregressive Processes Integrated of Order 2," Econometric Theory, 8, 188-202.

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