LimitedAssessed from the abstract
Fractional Brownian Motions, Fractional Noises and Applications
Benoît B. Mandelbrot, John W. Van Ness · SIAM Review · 1968
Why this label
- The provided text is a bibliographic/reference and citation listing for Mandelbrot and Van Ness's paper on fractional Brownian motions, not an abstract describing methods.
- No study design, sample size, randomization, blinding, or outcome details are stated in the text.
- The paper appears to be a theoretical/mathematical work (introducing 'Fractional Brownian Motions, Fractional Noises and Applications'), for which GRADE-style execution signals (randomization, dropout, etc.) are not applicable and are not described here.
The Paper Scorecard
- Standingclear
- No retraction on record (OpenAlex metadata as of 2026-07-03).
- Designjournal article
- Journal article (SIAM Review). Study design detail comes from the methodology read, not metadata.
- Executioninsufficient detail
- The provided text is a bibliographic/reference and citation listing for Mandelbrot and Van Ness's paper on fractional Brownian motions, not an abstract describing methods.
- No study design, sample size, randomization, blinding, or outcome details are stated in the text.
- The paper appears to be a theoretical/mathematical work (introducing 'Fractional Brownian Motions, Fractional Noises and Applications'), for which GRADE-style execution signals (randomization, dropout, etc.) are not applicable and are not described here.
- Corroborationfield confirmed
- Cited by 7703 works (OpenAlex citation count).
- Parallax's analysis of the paper's central finding found the weight of evidence SUPPORTS it (confidence: Emerging), with independent evidence streams beyond this paper.
- Provenanceidentified
- Published in SIAM Review.
- Publisher: Society for Industrial and Applied Mathematics.
- ISSN 0036-1445.
- The journal is not listed in DOAJ.
- Open-access status: closed.
The paper's central finding
“Fractional Brownian motions, defined as moving-average integrals of ordinary Brownian motion with a fractional-power kernel parameterized by H in (0,1), constitute self-similar Gaussian processes with stationary increments (fractional noises) whose correlations exhibit long-range dependence for H > 1/2.”