DOI10.1214/aos/1176348654zbMath0783.62032OpenAlexW2063653500MaRDI QIDQ1194537
Hans-Georg Müller
Publication date: 27 September 1992
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/aos/1176348654
Testing for Breaks in Regression Models with Dependent Data,
Model‐robust inference for continuous threshold regression models,
Discord Detection For A Process With A Predefined Interval Of Observations,
Interval and band estimation for curves with jumps,
Bootstrap test for change-points in nonparametric regression,
Estimation of change-points in a nonparametric regression function through kernel density estimation,
Estimation of the number of jumps of the jump regression functions,
Screening-assisted dynamic multiple testing with false discovery rate control,
Change point estimation in regression model with response missing at random,
ON MULTIPLE STRUCTURAL BREAKS IN DISTRIBUTION: AN EMPIRICAL CHARACTERISTIC FUNCTION APPROACH,
Variance estimation in nonparametric regression with jump discontinuities,
Multiresolution anomaly detection method for fractional Gaussian noise,
Testing discontinuities in nonparametric regression,
ACCURATE SIGNAL ESTIMATION NEAR DISCONTINUITIES,
Statistical methods for DNA sequence segmentation,
The wavelet identification for jump points of derivative in regression model,
Change-Point Estimation in Long Memory Nonparametric Models with Applications,
Asymptotics for change-point models under varying degrees of mis-specification,
A Bayesian wavelet approach to estimation of a change-point in a nonlinear multivariate time series,
Discussion on “Sequential Design and Estimation in Heteroscedastic Nonparametric Regression” by Sam Efromovich,
Bayesian Estimation of the Number of Change Points in Simple Linear Regression Models,
Discontinuities in robust nonparametric regression with α-mixing dependence,
Automatic bandwidth selection for modified m-smoother∗,
Estimation of regression functions with a discontinuity in a derivative with local polynomial fits,
Data-Driven Discontinuity Detection in Derivatives of a Regression Function,
Adaptive quantile regression with precise risk bounds,
Asymptotics for \(p\)-value based threshold estimation under repeated measurements,
Testing for change points in partially linear models,
Bayesian curve fitting for discontinuous functions using an overcomplete system with multiple kernels,
Adaptive estimation of autoregressive models with time-varying variances,
Nonparametric simultaneous testing for structural breaks,
Detections of changes in return by a wavelet smoother with conditional heteroscedastic volatility,
Wavelet estimation of a regression function with a sharp change point in a random design,
Local polynomial \(M\)-smoothers in nonparametric regression,
TESTING FOR STRUCTURAL CHANGE IN TIME-VARYING NONPARAMETRIC REGRESSION MODELS,
Change points in nonparametric regresion functions,
Nonparametric boundary detection,
Detecting Abrupt Changes by Wavelet Methods,
Two Non-Parametric Tests For Change-Point Problems. IDOPT Project: It is a joint project of CNRS, INRIA, UJF and INPG,
Change point estimation using nonparametric regression,
Nonparametric inference on jump regression surface,
Asymmetric cusp estimation in regression models,
Change-point estimation under adaptive sampling,
Two-stage change-point estimators in smooth regression models,
Change Point Estimation in Regression Models with Fixed Design,
Anatomical curve identification,
Testing for parameter stability in nonlinear autoregressive models,
Asymptotics for \(p\)-value based threshold estimation in regression settings,
On change-point estimation under Sobolev sparsity,
Glacier terminus estimation from Landsat image intensity profiles,
On the functional estimation of jump-diffusion models.,
A change-point problem in relative error-based regression,
Nonparametric estimation of the regression function having a change point in generalized linear models,
State-domain change point detection for nonlinear time series regression,
Jump estimation in inverse regression,
Detection of slightly expressed changes in random environment,
Change point detection for nonparametric regression under strongly mixing process,
Change point estimation by local linear smoothing under a weak dependence condition,
Asymptotic bias and variance of a kernel-based estimator for the location of a discontinuity,
Nonparametric inference on structural breaks,
Kernel estimation of discontinuous regression functions,
Change‐Point Tests for the Error Distribution in Non‐parametric Regression,
Regression discontinuity designs with unknown discontinuity points: testing and estimation,
Local linear kernel estimation of the discontinuous regression function,
Change point estimators by local polynomial fits under a dependence assumption,
A jump-detecting procedure based on spline estimation,
A change-point estimator using local Fourier series,
Semi-parametric dynamic time series modelling with applications to detecting neural dynamics,
Detection of a change point based on local-likelihood,
Optimal change-point estimation from indirect observations,
Propagation-separation approach for local likelihood estimation,
Asymptotic fluctuations of mutagrams,
Blind deconvolution for jump-preserving curve estimation,
Parameter Estimation of Some NHPP Software Reliability Models with Change-Point,
Asymptotic confidence sets for the jump curve in bivariate regression problems,
On rapid change points under long memory,
Kernel smoothers: an overview of curve estimators for the first graduate course in nonparametric statistics,
Singularity estimation via structural intensity: applications and modifications,
Tracking Edges, Corners and Vertices in an Image,
Jump-preserving regression and smoothing using local linear fitting: a compromise,
Kink estimation with correlated noise,
Change-point estimation from indirect observations. 1. Minimax complexity,
Nonlinear regression modeling and detecting change points via the relevance vector machine,
Consistencies and rates of convergence of jump-penalized least squares estimators,
On a multi-channel change-point problem,
A Statistical Test of Change-Point in Mean that Almost Surely Has Zero Error Probabilities,
Wavelet analysis of change-points in a non-parametric regression with heteroscedastic variance,
Non parametric derivative estimation with confidence bands,
Trend, Growth Rate, and Change Point Analysis—A Data Driven Approach,
Detection of linear and circular shapes in image analysis,
Jump detection in time series nonparametric regression models: a polynomial spline approach,
Estimation of a function with discontinuities via local polynomial fit with an adaptive window choice,
Minimax estimation of sharp change points,
Discontinuous versus smooth regression,
Jump detection in generalized error-in-variables regression with an application to Australian health tax policies,
A NEW VERSION OF THE LOCAL CONSTANT M-SMOOTHER,
A BAYESIAN ANALYSIS FOR DERIVATIVE CHANGE POINTS,
Estimation of a change point in the variance function based on the χ2-distribution,
KERNEL ESTIMATION WHEN DENSITY MAY NOT EXIST,
Rate of Convergence of a Change Point Estimator in a Misspecified Regression Model,
A jump-preserving curve fitting procedure based on local piecewise-linear kernel estimation,
Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators,
Change-point problems: bibliography and review,
Structural Adaptive Smoothing Procedures,
Estimation of a regression function with a sharp change point using boundary wavelets,
Limit theorems for kernel-type estimators for the time of change,
The wavelet detection of the jump and cusp points of a regression function,
Tracking a smooth fault line in a response surface.,
Asymptotics of M-estimators in two-phase linear regression models.,
Nonparametric monitoring of financial time series by jump-preserving control charts,
A variational inference for the Lévy adaptive regression with multiple kernels,
Discontinuous regression surfaces fitting,
Nonparametric estimation in change point hazard rate models for censored data: A counting process approach,
Detecting gradual changes in locally stationary processes,
Inference for single and multiple change-points in time series,
Semiparametric estimation for stationary processes whose spectra have an unknown pole,
Misspecified structural change, threshold, and Markov-switching models.,
Smooth change point estimation in regression models with random design,
Asymptotics of maximum likelihood estimator in a two-phase linear regression model,
Nonparametric multivariate breakpoint detection for the means, variances, and covariances of a discrete time stochastic process,
Change point estimation by local linear smoothing,
Testing for jumps in the presence of smooth changes in trends of nonstationary time series