Open AccessBook
The Analysis of Time Series: An Introduction
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TLDR
In this paper, simple descriptive techniques for time series estimation in the time domain forecasting stationary processes in the frequency domain spectral analysis bivariate processes linear systems state-space models and the Kalman filter non-linear models multivariate time series modelling some other topics.Abstract:
Simple descriptive techniques probability models for time series estimation in the time domain forecasting stationary processes in the frequency domain spectral analysis bivariate processes linear systems state-space models and the Kalman filter non-linear models multivariate time series modelling some other topics.read more
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Book ChapterDOI
Collective traffic forecasting
TL;DR: This work focuses on the simultaneous prediction of the congestion state at multiple lead times and at multiple nodes of a transport network, given historical and recent information, and forms the task in the supervised learning from interpretations setting and uses Markov logic networks with groundings-pecific weights to perform collective classification.
Journal ArticleDOI
The ubiquity of the rms-flux relation in black hole X-ray binaries
TL;DR: In this article, the authors investigated the short-term linear relation between the rms variability and the flux in 1961 observations of nine black hole X-ray binaries and found a strong dependence of the flux intercept of the RMS-flux relation on source state; as the source transitions from hard state into the hard intermediate state, the intercept becomes strongly positive.
Journal ArticleDOI
Reducing demand uncertainty in the platelet supply chain through artificial neural networks and ARIMA models.
TL;DR: Predicting blood platelet demands based on artificial neural networks and auto-regressive integrated moving average models was indicated to be more accurate in predicting the uncertainties in demand than the baseline model used in Zahedan Blood Transfusion Center.
Journal ArticleDOI
Networks from Flows - From Dynamics to Topology
TL;DR: Analysing complex networks of prototypical flows and from time series data of the equatorial Pacific, it is found that the analytical model reproduces the most salient features of these networks and thus provides a general foundation of climate networks.
Dissertation
Zooplankton variability in the california current, 1951-1982
TL;DR: In this paper, seasonal and non-seasonal variations in zooplankton biomass in the California Current system are examined from CalCOFI measurements over the period 1951-82.