发帖
雷达卡
英文文献：Information Theoretic Estimators of the First-Order Spatial Autoregressive Model-一阶空间自回归模型的信息理论估计
英文文献作者：Perevodchikov, Evgeniy V.
英文文献摘要：
Information theoretic estimators for the first-order autoregressive model are considered. Extensive Monte Carlo experiments are used to compare finite sample performance of traditional and three information theoretic estimators including maximum empirical likelihood, maximum empirical exponential likelihood, and maximum log Euclidean likelihood. It is found that information theoretic estimators are robust to specification of spatial autocorrelation and dominate traditional estimators in finite samples. Finally, the proposed estimators are applied to an illustrative example of hedonic housing pricing.
研究了一阶自回归模型的信息理论估计量。广泛的蒙特卡罗实验被用来比较传统和三个信息理论估计的有限样本性能，包括最大经验似然，最大经验指数似然，和最大对数欧氏似然。结果表明，信息理论估计器对空间自相关的定义具有较强的鲁棒性，在有限样本条件下优于传统估计器。最后，将所提出的估计器应用于一个享乐型住房定价的例子。
京公网安备 11010802022788号
