High-dimensional data segmentation in regression settings permitting temporal dependence and non-Gaussianity
Author:
Affiliation:
1. School of Mathematics, University of Bristol, Bristol, BS8 1UG
Publisher
Institute of Mathematical Statistics
Reference47 articles.
1. Yau, C. Y. and Zhao, Z. (2016). Inference for multiple change points in time series via likelihood ratio scan statistics. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 78 895–916.
2. BAI, J. and PERRON, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica 47–78.
3. RINALDO, A., WANG, D., WEN, Q., WILLETT, R. and YU, Y. (2021). Localizing changes in high-dimensional regression models. In International Conference on Artificial Intelligence and Statistics 2089–2097. PMLR.
4. Eichinger, B. and Kirch, C. (2018). A MOSUM procedure for the estimation of multiple random change points. Bernoulli 24 526–564.
5. Loh, P.-L. and Wainwright, M. J. (2012). High-dimensional regression with noisy and missing data: Provable guarantees with nonconvexity. The Annals of Statistics 40 1637–1664.
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3