Results 21 to 30 of about 188,817 (310)
Kernel Methods for Nonlinear Connectivity Detection
Entropy, 2019 In this paper, we show that the presence of nonlinear coupling between time series may be detected using kernel feature space F representations while dispensing with the need to go back to solve the pre-image problem to gauge model adequacy.
Lucas Massaroppe, Luiz A. Baccalá
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Estimation of Right-censored SETAR-type Nonlinear Time-series Model [PDF]
E3S Web of Conferences, 2023 This paper focuses on estimating the Self-Exciting Threshold Autoregressive (SETAR) type time-series model under right-censored data. As is known, the SETAR model is used when the underlying function of the relation-ship between the time-series itself ...
Ahmed Syed Ejaz +2 more
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International Journal of Distributed Sensor Networks, 2021 Time series have broad usage in the wireless Internet of Things. This article proposes a nonlinear time series prediction algorithm based on the Small-World Scale-Free Network after the AIC-Optimized Subtractive Clustering Algorithm (AIC-DSCA-SSNET, AD ...
Banteng Liu +7 more
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Forecasting With Nonlinear Time Series Models [PDF]
SSRN Electronic Journal, 2010 AbstractThis article considers nonlinear forecasting models, such as switching-regime models. These models are typically “small” compared to vector autoregressive and factor models, being either univariate or single-equation models, but tend to nest a linear relationship and so invite an assessment of whether allowing for nonlinearity improves forecast
Timo Terasvirta, Anders Bredahl Kock
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Nonlinear Error Correction Models [PDF]
, 2002 The relationship between cointegration and error correction (EC) models is well characterized in a linear context, but the extension to the nonlinear context is still a challenge.
Escribano, Álvaro, Mira, Santiago
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Presenting a new hybrid method for predicting the Stock Exchange price inde [PDF]
تحقیقات مالی, 2017 The trend of the stock price index, has taken as one of the investment criteria consistently. Because of the two components of nonlinear and time series price index volatility, in this study, a new hybrid model presented that can predict move and change ...
Diako Dorodi, Seyed Babak Abrahimi
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Inference for nonlinear epidemiological models using genealogies and time series. [PDF]
PLoS Computational Biology, 2011 Phylodynamics - the field aiming to quantitatively integrate the ecological and evolutionary dynamics of rapidly evolving populations like those of RNA viruses - increasingly relies upon coalescent approaches to infer past population dynamics from ...
David A Rasmussen +2 more
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Nonlinear Time Series Modelling: An Introduction [PDF]
Journal of Economic Surveys, 1999 Recent developments in nonlinear time series modelling are reviewed. Three main types of nonlinear model are discussed: Markov Switching, Threshold Autoregression and Smooth Transition Autoregression. Classical and Bayesian estimation techniques are described for each model.
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A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship [PDF]
Hydrology and Earth System Sciences, 2020 Wavelet coherence is a method that is commonly used in hydrology to extract scale-dependent, nonstationary relationships between time series. However, we show that the method cannot always determine why the time-domain correlation between two time series
J. Schulte, F. Policielli, B. Zaitchik
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Contribution of solitons to enhanced rogue wave occurrence in shallow depths: a case study in the southern North Sea [PDF]
Natural Hazards and Earth System Sciences, 2023 The shallow waters off the coast of Norderney in the southern North Sea are characterised by a higher frequency of rogue wave occurrences than expected. Here, rogue waves refer to waves exceeding twice the significant wave height.
I. Teutsch +3 more
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