标题： 白噪声假设的鲁棒自适应最优检验 显示英文标题

标题： Robust Adaptive Rate-Optimal Testing for the White Noise Hypothesis

摘要： 提出了一种新的检验方法来检验弱白噪声原假设。该检验基于Box-Pierce或Hong检验统计量阶数的一种新自动选择方法。该检验使用Lobato（2001）或Kuan和Lee（2006）的HAC临界值。数据驱动的阶数选择专门用于检测一类新的备择假设，其中只要数量足够，自相关系数可以是$o(n^{-1/2})$。模拟实验表明，该检验在弱白噪声原假设和备择假设下均表现出良好的行为。 显示英文摘要

摘要： A new test is proposed for the weak white noise null hypothesis. The test is based on a new automatic choice of the order for a Box-Pierce or Hong test statistic. The test uses Lobato (2001) or Kuan and Lee (2006) HAC critical values. The data-driven order choice is tailored to detect a new class of alternatives with autocorrelation coefficients which can be $o(n^{-1/2})$ provided there are enough of them. A simulation experiment illustrates the good behavior of the test both under the weak white noise null and the alternative.