| DC 欄位 |
值 |
語言 |
| DC.contributor | 統計研究所 | zh_TW |
| DC.creator | 邵莉雅 | zh_TW |
| DC.creator | Li-Ya Shao | en_US |
| dc.date.accessioned | 2003-6-26T07:39:07Z | |
| dc.date.available | 2003-6-26T07:39:07Z | |
| dc.date.issued | 2003 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=90225019 | |
| dc.contributor.department | 統計研究所 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 隨著科技的進步，各行各業的資料可能數以”億”計。但在極大集資料分析上，受計算工具儲存容量的限制，使得傳統的方法不可行。本文提出分段加權最小平方法來取代傳統的迴歸方法。我們將資料予以分組，先在各區段中估計迴歸係數，再將各段迴歸係數估計量的變異數加入考慮，使得較大變異區段之估計量具有較小的權重，進而探討估計量之性質。另外並提出一檢定迴歸係數之分段檢定法以及切斷分割原理和選擇變數的方法。 | zh_TW |
| dc.description.abstract | Many classical methods are not used for large data base . This paper is base on the statistic point to analysis the large data base . We prefer three regression methods to analysis data of large data base. | en_US |
| DC.subject | 龐大資料集 | zh_TW |
| DC.subject | 迴歸 | zh_TW |
| DC.subject | 資料挖掘 | zh_TW |
| DC.subject | Large data base | en_US |
| DC.subject | Data Mining | en_US |
| DC.subject | regression | en_US |
| DC.title | 龐大資料集之線性迴歸分析 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Linear regression for large data base. | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |