請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/2533完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 銀慶剛 | |
| dc.contributor.author | Hsueh-Han Huang | en |
| dc.contributor.author | 黃學涵 | zh_TW |
| dc.date.accessioned | 2021-05-13T06:41:35Z | - |
| dc.date.available | 2020-07-13 | |
| dc.date.available | 2021-05-13T06:41:35Z | - |
| dc.date.copyright | 2017-07-13 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-06-19 | |
| dc.identifier.citation | Abhirup Datta and Hui Zou. (2016). CoCoLasso for High-dimensional Error-in-variables Regression. https://arxiv.org/abs/1510.07123.
Alexandre Belloni, Mathieu Rosenbaum and Alexandre B.Tsybakov.(2014). An {l1; l2; linfinite}-Regularization Approach to High-Dimensional Errors-in-variables Models. https://arxiv.org/abs/1412.7216. Alexandre Belloni, Mathieu Rosenbaum and Alexandre B.Tsybakov. (2016). Linear and Conic Programming Estimators in High-Dimensional Errors-in variables Models. https://arxiv.org/abs/1408.0241. Ching-Kang Ing and Tze Leung Lai (2011). A stepwise regression method and consistent model selection for high-dimensional sparse linear models. Statist.Sinica,1473-1513. Ching-Kang Ing and Kunling Huang (2016). Model Selection for High-Dimensional Multivariate Time Dependent Models (Unpublished master's thesis). National Taiwan University, Taipei City. C.Z.Wei. (1987). Adaptive prediction by least squares predictors in stochastic regression models with applications to time series. Ann.Statist.15(4):1667-1682. David F.Findley and Ching-Zong Wei.(1993).Moment bounds for deriving time series CLTs and model selection procedures. Statist.Sinica,453-480. Po-Ling Loh and Martin J. Wainwright.(2012).High-dimensional regression with noisy and missing data:Provable guarantees with nonconvexity. Ann.Statist.40(3):1637-1664. Temlyakov,V.N .(2000).Weak greedy algorithms. Adv.Comput.Math.12,213-227. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/2533 | - |
| dc.description.abstract | We use a fast stepwise regression method, called orthogonal greedy algorithm (OGA) to select variables for high-dimensional time series model with measurement errors. Under a weak sparsity condition, we derive a convergence rate of OGA, which is expressed in terms of the number of iterations, the sample size and the order of the moment imposed on the error process. Under a strong sparsity condition, we develop a consistent model selection procedure using OGA and a high-dimensional information criterion. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-13T06:41:35Z (GMT). No. of bitstreams: 1 ntu-106-R04246010-1.pdf: 934153 bytes, checksum: 8f236e923d3d1cbaaf4134fc3858ba37 (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | 中文摘要………………………………………………………………………… i
英文摘要…………………………………………………………………………. ii 1.Introduction………………………………………………………………….. 1 2.OGA and Noiseless OGA……………………………………………….. 3 3.Uniform Convergence Rate of Empirical Prediction Error……………………... 4 4.Sure Screening Property and Model Selection Consistency…………………….. 9 5.Simulation Studies……………………………………………….. 16 參考文獻…………………………………………………………………….…… 23 附錄………………………………………………………………………..………. .24 | |
| dc.language.iso | en | |
| dc.subject | 時間序列 | zh_TW |
| dc.subject | 高維度 | zh_TW |
| dc.subject | 測量誤差 | zh_TW |
| dc.subject | 正交化貪婪演算法 | zh_TW |
| dc.subject | 稀疏性 | zh_TW |
| dc.subject | High-dimensional | en |
| dc.subject | sparsity | en |
| dc.subject | time series | en |
| dc.subject | measurement error | en |
| dc.subject | OGA | en |
| dc.title | 高維度時間序列並帶有測量誤差模型之模型選擇 | zh_TW |
| dc.title | Model Selection for High-Dimensional Time Series Models with Measurement Errors | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 105-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 俞淑惠,黃信誠,徐南蓉,鄭又仁 | |
| dc.subject.keyword | 高維度,測量誤差,正交化貪婪演算法,稀疏性,時間序列, | zh_TW |
| dc.subject.keyword | High-dimensional,measurement error,OGA,sparsity,time series, | en |
| dc.relation.page | 30 | |
| dc.identifier.doi | 10.6342/NTU201700925 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2017-06-19 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 應用數學科學研究所 | zh_TW |
| 顯示於系所單位： | 應用數學科學研究所 | |
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|---|---|---|---|
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