The following pages link to (Q3562793):
Displaying 21 items.
- Two-stage data segmentation permitting multiscale change points, heavy tails and dependence (Q92617) (← links)
- Detecting and estimating changes in dependent functional data (Q432320) (← links)
- Robust monitoring of CAPM portfolio betas. II (Q458632) (← links)
- TFT-bootstrap: resampling time series in the frequency domain to obtain replicates in the time domain (Q638798) (← links)
- Bootstrap and permutation tests of independence for point processes (Q892249) (← links)
- High dimensional efficiency with applications to change point tests (Q1642675) (← links)
- Abrupt change in mean using block bootstrap and avoiding variance estimation (Q1695533) (← links)
- Bootstrap change point testing for dependent data (Q1793896) (← links)
- Evaluating stationarity via change-point alternatives with applications to fMRI data (Q1940029) (← links)
- Adaptive quantile computation for Brownian bridge in change-point analysis (Q2072415) (← links)
- Nuisance-parameter-free changepoint detection in non-stationary series (Q2195742) (← links)
- Changepoint in dependent and non-stationary panels (Q2208373) (← links)
- A note on Studentized confidence intervals for the change-point (Q2430243) (← links)
- \(M\)-procedures for detection of a change under weak dependence (Q2448799) (← links)
- Block permutation principles for the change analysis of dependent data (Q2455733) (← links)
- On the detection of changes in autoregressive time series. II: Resampling procedures (Q2480024) (← links)
- Bootstrapping confidence intervals for the change-point of time series (Q3552859) (← links)
- Subsampling for General Statistics under Long Range Dependence with application to change point analysis (Q4571205) (← links)
- M-Procedures for Detection of Changes for Dependent Observations (Q4905901) (← links)
- Delay time in monitoring jump changes in linear models (Q5299460) (← links)
- A data-driven approach to detecting change points in linear regression models (Q6626120) (← links)
