Quantile spectral processes: asymptotic analysis and inference

DOI10.3150/15-BEJ711zbMath1369.62245arXiv1401.8104OpenAlexW3105232361MaRDI QIDQ282565

Tobias Kley, Stanislav Volgushev, Marc Hallin, Dette, Holger

Publication date: 12 May 2016

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1401.8104

zbMATH Keywords

weak convergencetime seriescopulasGaussian processesranksspectral analysisperiodogramGini spectraquantile spectral processes

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and spectral analysis (62M15)

Related Items (17)

The cross-quantilogram: measuring quantile dependence and testing directional predictability between time series ⋮ Automatic estimation of spatial spectra via smoothing splines ⋮ Statistical inference for quantiles in the frequency domain ⋮ On the unbiased asymptotic normality of quantile regression with fixed effects ⋮ The bootstrap for testing the equality of two multivariate time series with an application to financial markets ⋮ A copula spectral test for pairwise time reversibility ⋮ Fourier Analysis of Serial Dependence Measures ⋮ Unnamed Item ⋮ Bayesian copula spectral analysis for stationary time series ⋮ Quantile regression: A short story on how and why ⋮ A distribution free test for changes in the trend function of locally stationary processes ⋮ Robust tests for time series comparison based on Laplace periodograms ⋮ Model assessment for time series dynamics using copula spectral densities: a graphical tool ⋮ Composite Quantile Periodogram for Spectral Analysis ⋮ Robust fuzzy clustering based on quantile autocovariances ⋮ Quantile-based fuzzy \(C\)-means clustering of multivariate time series: robust techniques ⋮ The integrated copula spectrum

Uses Software

• robustbase
• quantspec
• quantilogram

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