| 研究生: |
陳彬 Ben Chen |
|---|---|
| 論文名稱: |
型1設限下韋伯參數估計問題 |
| 指導教授: |
呂理裕
Lii-Yuh Leu |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
理學院 - 統計研究所 Graduate Institute of Statistics |
| 畢業學年度: | 91 |
| 語文別: | 中文 |
| 論文頁數: | 53 |
| 中文關鍵詞: | 韋伯分配 、極值分配 、信賴區間 、型1設限 |
| 相關次數: | 點閱:20 下載:0 |
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關於型I設限資料下,韋伯分配參數的估計方法,本文採用最大概似估計量作為參數的點估計,而區間估計方面,除了傳統上利用大樣本性質,以近似常態法估計信賴區間外,另考量分別以log-likelihood檢定統計量為基礎、以及Bootstrap方法為基礎,共呈現十種方法估計參數之信賴區間。
為比較各種方法之優劣,本文透過模擬範例,以區間之平均長度和覆蓋機率作為比較的依據。結果顯示當樣本數為小樣本時,傳統上採用近似常態法並非最好的估計方式,反觀以log-likelihood檢定統計量為基礎的四種方法,即使在觀察之樣本數少的時候,覆蓋機率皆可達到名義之水準,當中的SLR和Third-Order方法更可得到較小的信賴區間,因此是較佳的估計方式。在以Bootstrap為基礎的五種方法中,PBSRLLR方法表現良好,當觀察之樣本數少的時候,覆蓋機率可達到名義之水準,其他四種Bootstrap方法則不能。在區間長度的表現上,當觀察之樣本數小於9個的時候,PBSRLLR可以得到比SLR和Third-Order方法更小的信賴區間,在此條件下,PBSRLLR是較佳的估計方式。
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