Establishes a uniform Bahadur representation for sieve M-estimators under temporal dependence and constructs valid simultaneous confidence regions using Gaussian approximation and self-convolved bootstrap.
Biometrika , volume=
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A new tail dependence measure for linear processes with regularly varying distributions is introduced, incorporating persistence effects and validated via simulations and cryptocurrency data analysis.
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Simultaneous Inference for Nonlinear Time Series, a Sieve M-regression Approach
Establishes a uniform Bahadur representation for sieve M-estimators under temporal dependence and constructs valid simultaneous confidence regions using Gaussian approximation and self-convolved bootstrap.
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Measuring Tail Dependence in Linear Processes: Theory and Empirics
A new tail dependence measure for linear processes with regularly varying distributions is introduced, incorporating persistence effects and validated via simulations and cryptocurrency data analysis.