Model Selection for High-Dimensional Time Series Models with Measurement Errors
碩士 === 國立臺灣大學 === 應用數學科學研究所 === 105 === 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 t...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2017
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| Online Access: | http://ndltd.ncl.edu.tw/handle/422rmw |