A distribution free test for changes in the trend function of locally stationary processes
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Publication:2233554
DOI10.1214/21-EJS1871zbMath1476.62079arXiv2005.11132OpenAlexW3186230236MaRDI QIDQ2233554
Florian Heinrichs, Dette, Holger
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/2005.11132
Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Stationary stochastic processes (60G10)
Uses Software
Cites Work
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- Quantile spectral processes: asymptotic analysis and inference
- Local linear quantile estimation for nonstationary time series
- Testing for changes in multivariate dependent observations with an application to temperature changes
- Weak convergence and empirical processes. With applications to statistics
- Inference for modulated stationary processes
- Tail-greedy bottom-up data decompositions and fast multiple change-point detection
- Nonparametric statistical procedures for the changepoint problem
- Detecting relevant changes in the mean of nonstationary processes -- a mass excess approach
- Structural breaks in time series
- Inference for single and multiple change-points in time series
- Gaussian approximations for non-stationary multiple time series
- Beyond Parametrics in Interdisciplinary Research: Festschrift in Honor of Professor Pranab K. Sen
- Improvement of Kernel Type Density Estimators
- A Self-Normalized Approach to Confidence Interval Construction in Time Series
- Multiscale change point detection for dependent data
- Greedy Kernel Change-Point Detection
- Change Point Analysis of Correlation in Non-stationary Time Series
- Narrowest-Over-Threshold Detection of Multiple Change Points and Change-Point-Like Features
- Heteroscedasticity and Autocorrelation Robust Structural Change Detection
- Analysis of Non‐Stationary Modulated Time Series with Applications to Oceanographic Surface Flow Measurements
- Self-Normalization for Time Series: A Review of Recent Developments
- Multiscale Change Point Inference
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