We consider a stationary AR(1) process with ARCH(1) errors given by the stochastic difference equation $X_{t}=\alpha X_{t-1}+\sqrt{\beta +\lambda X_{t-1}^{2 ...
The regression model with autocorrelated disturbances is as follows: In these equations, y t are the dependent values, x t is a column vector of regressor variables, is a column vector of structural ...
Asymptotic theory for heteroskedasticity autocorrelation consistent (HAC) covariance matrix estimators requires the truncation lag, or bandwidth, to increase more slowly than the sample size. This ...
To compute the sample autocorrelation function when missing values are present, PROC ARIMA uses only cross products that do not involve missing values and employs divisors that reflect the number of ...
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