Statistical inference of covariance change points in gaussian model
Statistical inference of covariance change points in gaussian model
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DOI：
10.1080/0233188032000158817
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发表时间：
2004-02
期刊：
影响因子：
1.9
通讯作者：
Jie Chen;Arjun K. Gupta
中科院分区：
文献类型：
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作者：
Jie Chen;Arjun K. Gupta
In this paper, we study the testing and estimation of multiple covariance change points for a sequence of m-dimensional (m > 1) Gaussian random vectors by using the Schwarz information criterion (SIC). The unbiased SIC is also obtained. The asymptotic null distribution of the test statistic is derived. The result is applied to a simulated bivariate normal vector sequence (m = 2), and changes are successfully detected.
