这种局部采用专门技术或实践的方式可以对其提供更成功的检验，这比大爆炸(big - bang)方式要好得多。

This local adoption of specific technologies or practices might often provide a more successful proof of them than a big-bang approach.

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本文基于非参数回归模型的局部核权最小二乘法提出变量间非线性协整的一种非参数检验方法。

Based on the locally kernel weighted least squares fit of the nonparametric regression models, this paper presents the nonparametric testing method for nonlinear cointegration.

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我们证明了在原假设和局部对立假设之下随机加权统计量的条件渐近分布与检验统计量在原假设之下的渐近分布相同。

It is shown that, under both the null and the local alternatives, the random weighting statistics have the same asymptotic distribution as the original test statistic under the null hypotheses.

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