ArticleThe Journal of chemical physics2008
A general statistical test for correlations in a finite-length time series.
Article in The Journal of chemical physics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Subdomain dynamics enable chemical chain reactions in non-ribosomal peptide synthetases.Nature chemistry · 2024Article
- Structural distributions from single-molecule measurements as a tool for molecular mechanics.Chemical physics · 2012Article
- Conformational dynamics of single G protein-coupled receptors in solution.The journal of physical chemistry. B · 2011Article
- Dynamic active-site protection by the M. tuberculosis protein tyrosine phosphatase PtpB lid domain.Journal of the American Chemical Society · 2010Article
- Information-theoretical analysis of time-correlated single-photon counting measurements of single molecules.The journal of physical chemistry. A · 2009Article
- Quantitative evaluation of cross correlation between two finite-length time series with applications to single-molecule FRET.The journal of physical chemistry. B · 2008Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The statistical properties of the autocorrelation function from a time series composed of independently and identically distributed stochastic variables has been studied. Analytical expressions for the autocorrelation function's variance have been derived. It has been found that two common ways of calculating the autocorrelation, moving-average and Fourier transform, exhibit different uncertainty characteristics. For periodic time series, the Fourier transform method is preferred because it gives smaller uncertainties that are uniform through all time lags. Based on these analytical results, a statistically robust method has been proposed to test the existence of correlations in a time series. The statistical test is verified by computer simulations and an application to single-molecule fluorescence spectroscopy is discussed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.