Strong Consistency of Parameter Estimates for Purely Explosive Autoregressive Models with Exogenous Inputs

摘要：

　　Asymptotic properties and strong consistency in the analysis of recursive estimation for stochastic regression models are important and fundamental.However,almost all of the existing results concerning the strong consistency of the least-squares estimates are established for non-explosive autoregressive models with exogenous inputs under the persistent excitation condition.In this paper,we establish the strong consistency of least-squares parameter estimates for explosive autoregressive models with persistently exciting exogenous inputs.

关键词： Least-squares Estimates Strong Consistency ARX Models Purely Explosive

作者: Taiyao Wang Bo Qi

作者单位: Key Laboratory of Systems and Control,ISS,Academy of Mathematics and Systems Science,CAS,Beijing 100 Key Laboratory of Systems and Control,ISS,Academy of Mathematics and Systems Science,CAS,Beijing 100

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 6588-6592

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）