期刊文献+

半参数变系数回归模型的空间相关性检验 被引量:3

Testing Spatial Correlation in Semi-parametric Varying Coefficient Regression Models
下载PDF
导出
摘要 本文对半参数变系数回归模型,构造了新的空间相关性检验统计量,利用三阶矩χ2逼近方法导出了其检验p-值的近似计算公式,蒙特卡罗模拟结果表明,该统计量在检测空间相关性方面具有较高的准确性和可靠性。同时考察了误差项服从不同分布时的检验功效,体现出该检验方法的稳健性。进一步,我们还给出了检验统计量的Bootstrap方法以及检验水平的模拟效果。 Based on the semi-parametric varying coefficient regression model,a new testing statistic for spatial correlation is constructed. The corresponding approximation of p-value is derived by employing the third-moment χ2method.The Monte Carlo simulation studies show that the proposed testing statistic has good accuracy and reliability. Meanwhile,we investigate the simulation results of testing powers for different error terms,which show that the testing method has high robustness. Furthermore,the bootstrap method and simulation results for the testing statistic are given.
出处 《统计研究》 CSSCI 北大核心 2015年第7期87-92,共6页 Statistical Research
基金 教育部人文社会科学项目“空间自回归单指数模型的理论和实践”(13YJA9100002)的阶段性成果
关键词 半参数变系数回归模型 空间相关性 BOOTSTRAP方法 Semi-parametric Varying Coefficient Regression Model Spatial Correlation Bootstrap Method
  • 相关文献

参考文献15

  • 1Anselin L. Spatial econometrics: methods and models [M]. Kluwer Academic, Dordrecht, 1988.
  • 2Cordy C B, D A Griffith. Efficiency of least squares estimators in the presence of spatial autocorrelation [J]. Communications in Statistics: Simulation and Computation, 1993, 22 (4): 1161 -1179.
  • 3Fan J, T Huang. Profile likelihood inferences on semiparametric varying-coefficient partially linear models [J]. Bernoulli, 2005, 11 (6): 1031 -1057.
  • 4Fan J, THuang, R Z Li. Analysis of longitudinal data with semiparametric estimation of covariance function [J]. Journal of the American Statistical Association, 2007, 102 (478) : 632 - 641.
  • 5Hu X M, Wang Z Z, Liu F. Zero finite-order serial correlation test in a semi-parametric varying-coefficient partially linear errors-invariables model [J]. Statistics and Probability Letters, 2008, 78 (12) : 1560 - 1569.
  • 6Imhof J P. Computing the distribution of quadratic forms in normal variables [J]. Biometrika, 1961,3 -4(48): 419 -426.
  • 7Li D, J Chen, Z Lin. Statistical inference in partially time-varying coefficient models [J]. Journal of Statistical Planning and Inference, 2011, 141: 995 -1013.
  • 8Pearson E S. Note on an approximation to the distribution of noncentral '1..2 [J]. Biometrika, 1959, 46: 364.
  • 9Xia Y, W Zhang, H Tong. Efficient estimation for semi varyingcoefficient models [J]. Biometrika, 2004, 91(3): 661 -681.
  • 10Zhang W, S Y Lee, X Song. Local polynomial fitting in semi varying coefficient models [J]. Journal of Multivariate Analysis, 2002, 82 (1) : 166 - 188.

二级参考文献65

  • 1刘锋,陈敏,邹捷中.部分线性模型序列相关的经验似然比检验[J].应用数学学报,2006,29(4):577-586. 被引量:14
  • 2Anselin, L. , 1988, Spatial Econometrics : Methods and Models [M], Kluwer, Dordrecht.
  • 3Anselin, L. and A. K. Bera, R. J. G. M. Florax, and M. Yoon, 1996, Simple Diagnostic Tests for Spatial Dependence [J], Regional Sceience and Urban Economics, 26, 77-104.
  • 4Anselin, L. and R. Florax, 1995, Small Sample Properties of Tests for Spatial Dependence in Regression Models : Some Further Results [C], New Directions in Spatial Econometrics. Spinger Verlag, New York, 21-74.
  • 5Chang, Y. , 2004, Bootstrap Unit Root Tests in Panels with Cross-sectional Dependency [J]. Journal of Econometrics, 120, 263-293.
  • 6Cliff, A. and J. Ord, 1973, Spatial Autocorrelation [M], Pion, London,
  • 7Cliff, A. and J. Ord, 1981, Spatial Processes, Models and Applications[M], Pion, London,
  • 8Davidson, R. and J. G. MaeKinnon, 1999, The Size Distortion of Bootstrap Tests [J], Econometric Theory, 15, 361-376.
  • 9Davidson, R. and J.G. MacKinnon, 2002, Bootstrap Tests : How Many Bootstraps[J].Econometric Reviews, 19, 55-68.
  • 10Davison, A.C. , D.V. Hinkley, and G. A. Young, 2003, Recent Developments in Bootstrap Methodology [J], Statistical Science, 18, 141-157.

共引文献20

同被引文献18

引证文献3

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部