| dc.contributor | 統計系 | en_US |
| dc.creator (作者) | 黃子銘 | zh_TW |
| dc.creator (作者) | Cheng, Yu-Hsiang ; Huang, Tzee-Ming | en_US |
| dc.date (日期) | 2012.05 | en_US |
| dc.date.accessioned | 8-Jul-2014 17:21:12 (UTC+8) | - |
| dc.date.available | 8-Jul-2014 17:21:12 (UTC+8) | - |
| dc.date.issued (上傳時間) | 8-Jul-2014 17:21:12 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/67383 | - |
| dc.description.abstract (摘要) | In Huang (2010) [8], a test of conditional independence based on maximal nonlinear conditional correlation is proposed and the asymptotic distribution for the test statistic under conditional independence is established for IID data. In this paper, we derive the asymptotic distribution for the test statistic under conditional independence for αα-mixing data. The results of simulation show that the test performs reasonably well for dependent data. We also apply the test to stock index data to test Granger noncausality between returns and trading volume. | en_US |
| dc.format.extent | 334565 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.language.iso | en_US | - |
| dc.relation (關聯) | Journal of Multivariate Analysis, 107, 210-226 | en_US |
| dc.subject (關鍵詞) | Conditional independence test; αα-mixing; Maximal conditional nonlinear correlation | en_US |
| dc.title (題名) | A conditional independence test for dependent data based on maximal conditional correlation | en_US |
| dc.type (資料類型) | article | en |
| dc.identifier.doi (DOI) | 10.1016/j.jmva.2012.01.017 | en_US |
| dc.doi.uri (DOI) | http://dx.doi.org/http://dx.doi.org/10.1016/j.jmva.2012.01.017 | en_US |
