Testing equality of spectral densities using randomization techniques

DOI10.3150/13-BEJ584zbMath1320.62081arXiv1506.00827OpenAlexW1989125161MaRDI QIDQ2348723

Markus Pauly, Carsten Jentsch

Publication date: 15 June 2015

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1506.00827

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (16)

A computational technique to classify several fractional Brownian motion processes ⋮ Nonparametric change point detection in multivariate piecewise stationary time series ⋮ A computational method to compare spectral densities of independent periodically correlated time series ⋮ Permutation‐based tests for discontinuities in event studies ⋮ Tests for comparing time‐invariant and time‐varying spectra based on the Anderson–Darling statistic ⋮ A computational bootstrap procedure to compare two dependent time series ⋮ 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 ⋮ Permutation testing for dependence in time series ⋮ Flexible nonlinear inference and change-point testing of high-dimensional spectral density matrices ⋮ Comparing spectral densities of stationary time series with unequal sample sizes ⋮ A similarity measure for second order properties of non-stationary functional time series with applications to clustering and testing ⋮ A note on using periodogram-based distances for comparing spectral densities ⋮ Robust tests for time series comparison based on Laplace periodograms ⋮ Model assessment for time series dynamics using copula spectral densities: a graphical tool ⋮ Testing equality of spectral densities using randomization techniques

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Testing temporal constancy of the spectral structure of a time series
• A note on testing hypotheses for stationary processes in the frequency domain
• A note on using periodogram-based distances for comparing spectral densities
• A periodogram-based metric for time series classification
• A central limit theorem for generalized quadratic forms
• Comparing nonparametric versus parametric regression fits
• How do bootstrap and permutation tests work?
• Asymptotic theory of statistical inference for time series
• Comparison of non-stationary time series in the frequency domain
• Regular variation of GARCH processes.
• Nonparametric approach for non-Gaussian vector stationary processes
• Comparing spectral densities of stationary time series with unequal sample sizes
• Testing equality of spectral densities using randomization techniques
• A test for stationarity based on empirical processes
• Testing nonparametric and semiparametric hypotheses in vector stationary processes
• Bootstrapping Frequency Domain Tests in Multivariate Time Series with an Application to Comparing Spectral Densities
• A new frequency domain approach of testing for covariance stationarity and for periodic stationarity in multivariate linear processes
• NON-PARAMETRIC APPROACH IN TIME SERIES ANALYSIS
• ASYMPTOTICS OF SPECTRAL DENSITY ESTIMATES
• Comparison of Times Series with Unequal Length in the Frequency Domain
• TESTS FOR COMPARING TWO ESTIMATED SPECTRAL DENSITIES
• DETERMINING THE BANDWIDTH OF A KERNEL SPECTRUM ESTIMATE
• DISCRIMINATING BETWEEN TWO SPECTRAL DENSITIES IN CASE OF REPLICATED OBSERVATIONS
• Automatic Frequency Domain Inference on Semiparametric and Nonparametric Models
• Nonparametric Comparison of Cumulative Periodograms
• Spectral Density Based Goodness‐of‐Fit Tests for Time Series Models
• Nonlinear system theory: Another look at dependence
• Testing Statistical Hypotheses
• Testing the Fit of a Vector Autoregressive Moving Average Model

This page was built for publication: Testing equality of spectral densities using randomization techniques