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 ...

This is a preview. Log in through your library . Abstract The estimation of spatial autocorrelation in spatially- and temporally-referenced data is fundamental to understanding an organism's ...

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 ...

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 ...