Robust Adaptive Rate-Optimal Testing for the White Noise Hypothesis

Details Robust Adaptive Rate-Optimal Testing for the White Noise Hypothesis Robust Adaptive Rate-Optimal Testing for the White Noise Hypothesis

2011-06-10

arxiv.org/abs/1106.2014v2

Mathematics

Statistics Theory

Article plus Supplementary Material document which groups proofs

Scientific paper

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.

Affiliated with

Also associated with

No associations

Rating

Robust Adaptive Rate-Optimal Testing for the White Noise Hypothesis does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Robust Adaptive Rate-Optimal Testing for the White Noise Hypothesis, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Robust Adaptive Rate-Optimal Testing for the White Noise Hypothesis will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-320222