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The Measurement of Power Spectra
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This article is published in Physics Today.The article was published on 1960-02-01. It has received 1989 citations till now.read more
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Monte Carlo Sampling Methods Using Markov Chains and Their Applications
TL;DR: A generalization of the sampling method introduced by Metropolis et al. as mentioned in this paper is presented along with an exposition of the relevant theory, techniques of application and methods and difficulties of assessing the error in Monte Carlo estimates.
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Spectrum estimation and harmonic analysis
TL;DR: In this article, a local eigenexpansion is proposed to estimate the spectrum of a stationary time series from a finite sample of the process, which is equivalent to using the weishted average of a series of direct-spectrum estimates based on orthogonal data windows to treat both bias and smoothing problems.
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Testing for nonlinearity in time series: the method of surrogate data
TL;DR: In this article, a statistical approach for identifying nonlinearity in time series is described, which first specifies some linear process as a null hypothesis, then generates surrogate data sets which are consistent with this null hypothesis and finally computes a discriminating statistic for the original and for each of the surrogate sets.
Testing for nonlinearity in time series: The method of surrogate data
TL;DR: A statistical approach for identifying nonlinearity in time series which is demonstrated for numerical data generated by known chaotic systems, and applied to a number of experimental time series, which arise in the measurement of superfluids, brain waves, and sunspots.
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The structure of turbulent boundary layers
TL;DR: In this article, the authors describe the formation of low-speed streaks in the region very near the wall, which interact with the outer portions of the flow through a process of gradual lift-up, then sudden oscillation, bursting, and ejection.