Finite sample properties of maximum likelihood estimator in spatial models
Finite sample properties of maximum likelihood estimator in spatial models
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DOI：
10.1016/j.jeconom.2005.08.006
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发表时间：
2007-04-01
影响因子：
6.3
通讯作者：
Ullah, Aman
中科院分区：
文献类型：
--
作者：
Bao, Yong;Ullah, Aman
研究了空间自回归模型极大似然估计的有限样本性质。一个随机扩展的得分函数是用来开发的二阶偏差和均方误差的最大似然估计。我们表明，结果可以表示在期望的交叉产品的二次型，或比率的二次型在一个正常的向量，可以使用最高阶不变多项式进行评估。我们的数值计算表明，极大似然估计的二阶行为依赖于权重矩阵的稀疏程度。(C)2006 Elsevier B.V.保留所有权利。
We investigate the finite sample properties of the maximum likelihood estimator for the spatial autoregressive model. A stochastic expansion of the score function is used to develop the second-rder bias and mean squared error of the maximum likelihood estimator. We show that the results can be expressed in terms of the expectations of cross products of quadratic forms, or ratios of quadratic forms in a normal vector which can be evaluated using the top order invariant polynomial. Our numerical calculations demonstrate that the second-order behaviors of the maximum likelihood estimator depend on the degree of sparseness of the weights matrix. (C) 2006 Elsevier B.V. All rights reserved.