Publikationsserver
Confidence sets for change-point problems in nonparametric regression
In this thesis, confidence sets for different nonparametric regression problems with change-points are developed. Uniform and pointwise asymptotic confidence bands for the jump-location-curve in a boundary fragment model using methods from M-estimation and Gaussian approximation are constructed for...
Đã lưu trong:
| Tác giả chính: | |
|---|---|
| Tác giả khác: | |
| Định dạng: | Dissertation |
| Ngôn ngữ: | Tiếng Anh |
| Được phát hành: |
Philipps-Universität Marburg
2018
|
| Những chủ đề: | |
| Truy cập trực tuyến: | Bài toàn văn PDF |
| Các nhãn: |
Thêm thẻ
Không có thẻ, Là người đầu tiên thẻ bản ghi này!
|
| Tóm tắt: | In this thesis, confidence sets for different nonparametric regression problems with change-points are developed. Uniform and pointwise asymptotic confidence bands for the jump-location-curve in a boundary fragment model using methods from M-estimation and Gaussian approximation are constructed for the rotated difference kernel estimator. In addition, estimation of the location and of the height of the jump in some derivative of a regression curve is considered. Optimal convergence rates as well as the joint asymptotic normal distribution of estimators based on the zero-crossing-time technique are established over certain Hölder-classes. Further, joint as well as marginal asymptotic confidence sets which are honest and adaptive for these parameters over specific Hölder-classes are constructed. The finite-sample performance is investigated in simulation studies, and real data illustrations are given. |
|---|---|
| Mô tả vật lý: | 171 Seiten |
| DOI: | 10.17192/z2018.0511 |