The Bias of Estimators of Causal Spatial Autoregressive Processes
研究了在矩形格点上观测的二维因果自回归过程的Yule-Walker和最小二乘估计量的渐近分布，给出了Yule-Walker估计量渐近偏差的显式表达式，并证明使用无偏样本自协方差函数或最小二乘估计量可消除该偏差。
We study the asymptotic distribution of Yule-Walker and least squares estimators for twodimensional causal autoregressive processes observed on a rectangular part of a lattice. An explicit expression for the asymptotic bias of Yule-Walker estimators is obtained. It is shown that this bias disappears if we use the so-called unbiased sample autocovariance function or least squares estimators.