Journal Article
Spectral Analysis and Time Series
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In this article, the authors introduce the concept of Stationary Random Processes and Spectral Analysis in the Time Domain and Frequency Domain, and present an analysis of Processes with Mixed Spectra.Abstract:
Preface. Preface to Volume 2. Contents of Volume 2. List of Main Notation. Basic Concepts. Elements of Probability Theory. Stationary Random Processes. Spectral Analysis. Estimation in the Time Domain. Estimation in the Frequency Domain. Spectral Analysis in Practice. Analysis of Processes with Mixed Spectra.read more
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Stochastic Variation of Earthquake Ground Motion in Space and Time
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The size and power of the variance ratio test in finite samples: A Monte Carlo investigation
Andrew W. Lo,A. Craig MacKinlay +1 more
TL;DR: In this article, the authors examined the finite-sample properties of the variance ratio test of the random walk hypothesis via Monte Carlo simulations under two null and three alternative hypotheses, and compared the performance of the Dickey-Fuller t and the Box-Pierce Q statistics.
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Sieve bootstrap for time series
TL;DR: In this paper, a bootstrap method based on the method of sieves is proposed, where a linear process is approximated by a sequence of autoregressive processes of order p p(n), where p n), p n o (n) as the sample size n.
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A test for volatility spillover with application to exchange rates
Yongmiao Hong,Yongmiao Hong +1 more
TL;DR: The authors proposed a class of asymptotic N(0,1) tests for volatility spillover between two time series that exhibit conditional heteroskedasticity and may have infinite unconditional variances.
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DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents
TL;DR: In this paper, a Deep Stochastic IOC RNN Encoderdecoder framework, DESIRE, is proposed to predict future locations of objects in multiple scenes by accounting for the multi-modal nature of the future prediction (i.e., given the same context, future may vary).
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