
Approximations and asymptotics of continuoustime locally stationary processes
We introduce a general theory on stationary approximations for locally s...
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On the Underspread/Overspread Classification of Random Processes
We study the impact of the recently introduced underspread/overspread cl...
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Linear StateSpace Model with TimeVarying Dynamics
This paper introduces a linear statespace model with timevarying dynam...
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PLSO: A generative framework for decomposing nonstationary timeseries into piecewise stationary oscillatory components
To capture the slowly timevarying spectral content of realworld time s...
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Learning the Latent State Space of TimeVarying Graphs
From social networks to Internet applications, a wide variety of electro...
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The space of sections of a smooth function
Given a compact manifold X with boundary and a submersion f : X → Y whos...
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A Development of ContinuousTime Transfer Entropy
Transfer entropy (TE) was introduced by Schreiber in 2000 as a measureme...
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Continuoustime locally stationary time series models
We adapt the classical definition of locally stationary processes in discretetime to the continuoustime setting and obtain equivalent representations in the time and frequency domain. From this, a unique timevarying spectral density is derived using the WignerVille spectrum. As an example, we investigate timevarying Lévydriven state space processes, including the class of timevarying Lévydriven CARMA processes. First, the connection between these two classes of processes is examined. Considering a sequence of timevarying Lévydriven state space processes, we then give sufficient conditions on the coefficient functions that ensure local stationarity with respect to the given definition.
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