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双典型相关分析中的秩似然比检验AI 解读

The likelihood-ratio test for the hypothesis that the smallest of two canonical correlations is zero is Bartlett adjustable. This theoretical property says that the moments of the test criterion and of a scaled version of the asymptotic distribution have the same second-order expansion. Simulations show that scaling with the exact expectation improves the asymptotic distribution, but the expectation is approximated poorly by its second-order expansion. This can be explained…

自回归模型单位根检验的 Bartlett 修正AI 解读

The usual conditions for a Bartlett correction are not fulfilled when testing for a unit root in a Gaussian autoregressive model. However, by expanding the moments of the likelihood ratio statistic it can be shown that the Bartlett correction improves the asymptotic distribution approximation.