Estimation and inference of time-varying auto-covariance under complex trend: a difference-based approach

DOI10.1214/21-EJS1893zbMath1476.62077arXiv2003.05006MaRDI QIDQ2233573

Yanyan Li

Publication date: 11 October 2021

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2003.05006

zbMATH Keywords

change pointslocal stationarityGaussian approximationsimultaneous confidence bands

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Nonparametric estimation (62G05) Nonparametric tolerance and confidence regions (62G15)

Uses Software

• itsmr
• ITSM2000
• AR1seg

Cites Work

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• A robust approach for estimating change-points in the mean of an \(\mathrm{AR}(1)\) process
• Bandwidth choice for nonparametric regression
• Local linear quantile estimation for nonstationary time series
• Variance function estimation in multivariate nonparametric regression with fixed design
• Nonparametric inference of quantile curves for nonstationary time series
• Estimation of heteroscedasticity in regression analysis
• Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
• Subsampling
• Fitting time series models to nonstationary processes
• Local polynomial estimators of the volatility function in nonparametric autoregression
• On the choice of difference sequence in a unified framework for variance estimation in nonparametric regression
• On variance function estimation with quadratic forms
• Effect of mean on variance function estimation in nonparametric regression
• Variance estimation in nonparametric regression via the difference sequence method
• Introduction to Time Series and Forecasting
• Gaussian approximations for non-stationary multiple time series
• A Measure of Stationarity in Locally Stationary Processes With Applications to Testing
• A Flexible and Fast Method for Automatic Smoothing
• On multiple regression models with nonstationary correlated errors
• A Simple Estimator of Error Correlation in Non-parametric Regression Models
• Optimal difference-based variance estimation in heteroscedastic nonparametric regression
• Testing the Goodness of Fit of a Linear Model Via Nonparametric Regression Techniques
• Detecting Dependencies in Smooth Regression Models
• Choice of bandwidth for kernel regression when residuals are correlated
• Simultaneous Inference of Linear Models with Time Varying Coefficients
• A Test for Second-Order Stationarity and Approximate Confidence Intervals for Localized Autocovariances for Locally Stationary Time Series
• Using Difference-Based Methods for Inference in Nonparametric Regression with Time Series Errors
• A test for second-order stationarity of a time series based on the discrete Fourier transform
• Change Point Analysis of Correlation in Non-stationary Time Series
• Validating Stationarity Assumptions in Time Series Analysis by Rolling Local Periodograms
• Heteroscedasticity and Autocorrelation Robust Structural Change Detection
• Nonlinear system theory: Another look at dependence
• Autocovariance Estimation in Regression with a Discontinuous Signal and m‐Dependent Errors: A Difference‐Based Approach

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