Multiscale jump testing and estimation under complex temporal dynamics
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Publication:6565327
DOI10.3150/23-BEJ1677MaRDI QIDQ6565327
Publication date: 2 July 2024
Published in: Bernoulli (Search for Journal in Brave)
Cites Work
- Title not available (Why is that?)
- Testing for jumps in the presence of smooth changes in trends of nonstationary time series
- Nonparametric simultaneous testing for structural breaks
- Testing for structural change in regression quantiles
- Multiscale methods for shape constraints in deconvolution: confidence statements for qualitative features
- Synchrosqueezed wavelet transforms: an empirical mode decomposition-like tool
- Decision theoretic optimality of the cusum procedure
- Local linear quantile estimation for nonstationary time series
- Smooth approximations
- The asymptotic behavior of some nonparametric change-point estimators
- Change-points in nonparametric regression analysis
- Large deviations of heavy-tailed sums with applications in insurance
- Subsampling
- Change point estimation using nonparametric regression
- A note on Ritov's Bayes approach to the minimax property of the cusum procedure
- Fitting time series models to nonstationary processes
- Two-stage change-point estimators in smooth regression models
- Gradient-based structural change detection for nonstationary time series M-estimation
- Simultaneous confidence bands for linear regression and smoothing
- On the estimation of jump points in smooth curves
- Tail probabilities of the maxima of Gaussian random fields
- Statistical inference for time-varying ARCH processes
- Probability and moment inequalities under dependence
- Testing for smooth structural changes in time series models via nonparametric regression
- Algorithm 908
- Fast and Stable Multivariate Kernel Density Estimation by Fast Sum Updating
- The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
- Adaptive tests of regression functions via multiscale generalized likelihood ratios
- A jump-preserving curve fitting procedure based on local piecewise-linear kernel estimation
- Minimax kernels for nonparametric curve estimation
- Estimating and Testing Linear Models with Multiple Structural Changes
- An Adaptive, Rate-Optimal Test of a Parametric Mean-Regression Model Against a Nonparametric Alternative
- BOOTSTRAP-ASSISTED UNIT ROOT TESTING WITH PIECEWISE LOCALLY STATIONARY ERRORS
- A Self-Normalized Approach to Confidence Interval Construction in Time Series
- Confidence Sets in Change-Point Problems
- Optimal Detection of Changepoints With a Linear Computational Cost
- Multiscale change point detection for dependent data
- Multiscale Inference and Long-Run Variance Estimation in Non-Parametric Regression with Time Series Errors
- Change Point Analysis of Correlation in Non-stationary Time Series
- Testing for Change Points in Time Series
- Heteroscedasticity and Autocorrelation Robust Structural Change Detection
- Detecting Relevant Changes in Time Series Models
- Multiscale Change Point Inference
- On the Volume of Tubes
- Segmenting Time Series via Self-Normalisation
- Inference of Breakpoints in High-dimensional Time Series
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