Financial

Auto-Regressive

Auto-Regressive (AR) Process

A stationary stochastic process where the current value of the time series is related to the past p values, where p is any integer, is called an AR(p) process. When the current value is related to the previous two values, it is an AR(2) process. An AR(1) process has an infinite memory.
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References in periodicals archive
Study used Auto-regressive Distributive Lag (ARDL) technique to estimate the equation (2).
An auto-regressive (AR) model based error concealment scheme is proposed for stereoscopic video coding in [5].
The conventional time series prediction models mainly include ARMA (AR, MA), ARIMA, improved time series model Threshold Auto-Regressive (TAR), Vector Auto-Regression (VAR), Auto-Regressive Conditional Heteroscedasticity (ARCH), and Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH).
(Journal of Institutional Economics, 2016) showing spatial dependence in incomes and institutional quality within the U.S., we also estimated our model using the spatial auto-regressive (SAR) model with allowance for spatial autocorrelation in the error term.
For that purpose growth model was developed and regressed by applying different analytical techniques that includes unit root test, Auto-Regressive Distributed Lag Model, ARDL bound testing, Wald test, ARDL co-integration and long form.
In a state-of-the-art Bayesian time-varying parameter vector auto-regressive framework, the authors demonstrate the strong role of the dollar in shaping the oil price dynamics, an effect that is not widely accepted among energy experts who often consider oil as a pure exogenous variable.
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