
pmid: 32069526
An alternative analysis approach, namely, orthogonal detrended fluctuation analysis (ODFA), is proposed to quantify the long-range correlation exponent. This method uses an orthogonal polynomial to attenuate any trends and quantify the (auto-) correlations in the data. The method is tested using numerically simulated data with long-range correlation. A matrix formalism of this approach is also proposed. Furthermore, the extension to high-order polynomial detrending is discussed. The proposed approach quantifies the long-range exponent with an error rate of about 8% for short datasets (3000 samples) and an error rate of about 1% for long datasets (100 000 samples). ODFA can find applications that involve processing long datasets as well as in real-time processing.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
