
SUMMARY The task of estimating moments of the spectrum of a stationary time series, rather than the more common problem of estimating the spectrum itself, is discussed. In particular, explicit formulae are deduced for the mean and variance of an estimator of the normalized standard deviation of the spectrum. Besides its theoretical significance, the necessity for estimating such a moment is of practical importance, for example, in the analysis of the velocity distributions of turbulent phenomena.
Time series, auto-correlation, regression, etc. in statistics (GARCH), Inference from stochastic processes and spectral analysis
Time series, auto-correlation, regression, etc. in statistics (GARCH), Inference from stochastic processes and spectral analysis
| 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). | 13 | |
| 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). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
