Testing for Long-Range Dependence in the Presence of Shifting Means or a Slowly Declining Trend, Using a Variance-Type Estimator

Teverovsky, V., & Taqqu, M. (1997). Testing for Long-Range Dependence in the Presence of Shifting Means or a Slowly Declining Trend, Using a Variance-Type Estimator. Journal of Time Series Analysis, 279-304.

Type

Journal article

Intellectual base

Primary research

Year

1997

DOI

10.1111/1467-9892.00050

Link

https://doi.org/10.1111/1467-9892.00050

Cited by

1 citation across 1 artifact.

Domain-specific

• Hurst Exponent
  • Hu and colleagues show that linear, periodic, and power-law trends create crossovers in DFA through competition between noise scaling and apparent trend scaling. Teverovsky and Taqqu show how shifts in mean or a slowly declining trend can mislead a variance-type long-memory estimator.

Verification

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Registry ID ref:c56ded2a0014 · see in the full table