Results 61 to 70 of about 1,440,592 (123)
, 2021 Funding: The research of H. Chen was funded by China Scholarship Council (File No. 201906150102). J. M.Fraser was financially supported by an EPSRC Standard Grant (EP/R015104/1) and a Leverhulme Trust Research Project Grant (RPG-2019-034).Let pn denote ...
Chen, Haipeng +2 more
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Sequential Outlier Detection in Nonstationary Time Series
Journal of Time Series Analysis, EarlyView.ABSTRACT A novel method for sequential outlier detection in nonstationary time series is proposed. The method tests the null hypothesis of “no outlier” at each time point, addressing the multiple testing problem by bounding the error probability of successive tests, using extreme‐value theory. The asymptotic properties of the test statistic are studied
Florian Heinrichs +2 more
wiley +1 more source
Degenerate SDE with Hölder--Dini Drift and Non-Lipschitz Noise Coefficient
, 2016 The existence-uniqueness and stability of strong solutions are proved for a class of degenerate stochastic differential equations, where the noise coefficient might be non-Lipschitz, and the drift is locally Dini continuous in the component with noise (i.
Feng-yu Wang
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Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models
Journal of Time Series Analysis, EarlyView.ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
wiley +1 more source
Testing Distributional Granger Causality With Entropic Optimal Transport
Journal of Time Series Analysis, EarlyView.ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley +1 more source
Moving Aggregate Modified Autoregressive Copula‐Based Time Series Models (MAGMAR‐Copulas)
Journal of Time Series Analysis, EarlyView.ABSTRACT Copula‐based time series models can model univariate and stationary time series in a flexible way by decomposing the joint distribution of consecutive observations into a copula and the stationary distribution. Implicitly, this approach assumes a finite Markov order. In reality, a time series may not follow the Markov property.
Sven Pappert
wiley +1 more source
Parametric Time‐Variation in the Unconditional Volatility: Estimation and Inference
Journal of Time Series Analysis, EarlyView.ABSTRACT We propose modeling time‐variation in the unconditional volatility by augmenting the standard GARCH model by a deterministic time‐varying intercept. The model, called the additive time‐varying (ATV‐)GARCH model, can be interpreted as a reduced form of a model including covariates and can be derived from a multiplicative decomposition of ...
Niklas Ahlgren +2 more
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Asymptotics of Time‐Varying Processes in Continuous‐Time Using Locally Stationary Approximations
Journal of Time Series Analysis, EarlyView.ABSTRACT We introduce a general theory on stationary approximations for locally stationary continuous‐time processes. Based on the stationary approximation, we use θ$$ \theta $$‐weak dependence to establish laws of large numbers and central limit type results under different observation schemes.
Robert Stelzer, Bennet Ströh
wiley +1 more source
Hölder exponents of horocycle foliations on surfaces
, 1999 We show that the horocycle foliations on a compact $C^{\infty}$ (or even $C^{\omega}$) surface of non-positive curvature can fail to be Lipschitz, even if the curvature vanishes only along a single closed geodesic.
VIOREL NIŢICĂ, MARLIES GERBER
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Detecting Multiple Change Points in Linear Models With Heteroscedasticity
Journal of Time Series Analysis, EarlyView.ABSTRACT The problem of detecting change points in the parameters of a linear regression model with errors and covariates exhibiting heteroscedasticity is considered. Asymptotic results for weighted functionals of the cumulative sum (CUSUM) processes of model residuals are established when the model errors are weakly dependent and non‐stationary ...
Lajos Horváth +2 more
wiley +1 more source