| DC 欄位 |
值 |
語言 |
| DC.contributor | 統計研究所 | zh_TW |
| DC.creator | 蔡佩洹 | zh_TW |
| DC.creator | Pei-Yuan Tsai | en_US |
| dc.date.accessioned | 2016-6-17T07:39:07Z | |
| dc.date.available | 2016-6-17T07:39:07Z | |
| dc.date.issued | 2016 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=103225011 | |
| 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 | 本論文提出一個新的強韌概似函數方法來推論配對設計下兩個多項式分配的異同。我們利用強韌分數統計量檢定兩個多項式分配是否相同來展示此強韌概似法之優異性。此強韌法可以自動的考慮群集資料間的相關性，且在不需要知道正確的聯合分配下便可應用。在成對二元資料的情況下，強韌分數統計量正好就是著名的McNemar’s 檢定統計量。本文中也提出了理論證明，並利用模擬和實例分析來展示強韌化方法的優勢。 | zh_TW |
| dc.description.abstract | We propose a new robust likelihood approach for inference about the difference between two multinomial distributions in paired designs. The merit of this parametric robust method is illustrated by the robust score statistic for testing the equality of two multinomial distributions. This test accounts for the within-cluster correlation in a data-driven manner and is easy to compute without a full model specification. The robust score test reduces to the McNemar’s test in the paired binary data scenario. We provide theoretical justification and use simulations and real data analysis to demonstrate the superiority of the robust procedure. | en_US |
| DC.subject | 強韌概似函數 | zh_TW |
| DC.subject | 篩檢檢驗 | zh_TW |
| DC.subject | 配對設計 | zh_TW |
| DC.subject | 伯努力分配 | zh_TW |
| DC.subject | 多項式分配 | zh_TW |
| DC.subject | Robust likelihood | en_US |
| DC.subject | Diagnostic test | en_US |
| DC.subject | paired designs | en_US |
| DC.subject | Bernoulli distribution | en_US |
| DC.subject | Multinomial distribution | en_US |
| DC.title | 配對設計下多項分配比較之強韌推論 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | A robust inference of comparing multinomial distributions under paired designs | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |