Geometric Properties of AR(q) Nonlinear Regression Models

Chinese Quarterly Journal of Mathematics ›› 2004, Vol. 19 ›› Issue (2): 146-154.

Geometric Properties of AR(q) Nonlinear Regression Models

Department of Mathematics, Southeast University, Nanjing 210096, China; College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China

Received:2002-07-10 Online:2004-06-30 Published:2024-03-18
About author:LIU Ying-an(1965-),male,native of Shouxian,Anhui,an associate professor of Nanjing Forestry University,Ph.D.,engages in statistics;WEI Bo-cheng(1937-),male,native of Zhenjiang,Jiangsu,a professor of Southeast University,engages in statistics.
Supported by:
Supported by the NSSFC(02BTJ001)； Supported by the NSSFC(04BTJ002)； Supported by the Grant for Post-Doctorial Fellows in Southeast University；

Abstract

Abstract: This paper is devoted to a study of geometric properties of AR(q) nonlinear regression models. We present geometric frameworks for regression parameter space and autoregression parameter space respectively based on the weighted inner product by fisher information matrix. Several geometric properties related to statistical curvatures are given for the models. The results of this paper extended the work of Bates & Watts(1980,1988) [1,2] and Seber & Wild(1989) [3].

Key words: nonlinear , , regression , , model, AR(q)errors, geometric , , framework, statistical curvature, Fisher information matrix

CLC Number:

LIU Ying-an, WEI Bo-cheng . Geometric Properties of AR(q) Nonlinear Regression Models[J]. Chinese Quarterly Journal of Mathematics, 2004, 19(2): 146-154.

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Geometric Properties of AR(q) Nonlinear Regression Models

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