The asymptotic distribution of canonical correlations and variates in cointegrated models.
The asymptotic distribution of canonical correlations and variates in cointegrated models.
复制标题
协整模型中典型相关性和变量的渐近分布。
DOI：
10.1073/pnas.97.13.7068
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发表时间：
2000
影响因子：
11.1
通讯作者：
T. W. Anderson
中科院分区：
文献类型：
--
作者：
T. W. Anderson
本文所考虑的协整模型是一个非平稳的向量自回归过程，其中一些线性函数是平稳的，另一些是随机游动的。过程的第一个差异（“纠错形式”）是固定的。统计推断，如过程系数的降秩回归估计和平稳部分的维数假设检验，涉及过程过去的差向量和相关向量之间的典型相关。在过程为高斯过程的假设下，得到了典型相关和典型向量的渐近分布。
The cointegrated model considered here is a nonstationary vector autoregressive process in which some linear functions are stationary and others are random walks. The first difference of the process (the "error-correction form") is stationary. Statistical inference, such as reduced rank regression estimation of the coefficients of the process and tests of hypotheses of dimensionality of the stationary part, involves the canonical correlations between the difference vector and the relevant vector of the past of the process. The asymptotic distributions of the canonical correlations and the canonical vectors under the assumption that the process is Gaussian are found.