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題 名 | 離群值鑑定方法應用於作物區域試驗穩定性分析之例釋=A Demonstration of Outlier Detection on Stability Analysis of Crop Regional Trial |
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作 者 | 呂秀英; | 書刊名 | 中華農業研究 |
卷 期 | 49:2 2000.06[民89.06] |
頁 次 | 頁36-48 |
分類號 | 434 |
關鍵詞 | 區域試驗; 穩定性; 離群值診斷; 穩健迴歸; 再加權最小平方迴歸; Regional trial; Stability; Outlier diagnostics; Robust regression; Reweighted least squares regression; |
語 文 | 中文(Chinese) |
中文摘要 | 本省作物區域試驗一般採用的穩定性介量多以最受廣泛使用的直線迴歸分析法為主。由於傳統迴歸分析是以最小平方法(LS)來估計迴歸係數,對離群值(或異常值)之存在非常敏感,離群值之存在會造成迴歸係數估計不良,也會造成直線迴歸分析殘差均方異質,從而可能影響穩定性分析之準確度。現行用以診斷群值的統計方法甚多,可區分為兩大類別:傳統的迴歸診斷及最新發展的穩健迴歸。然而,它們卻從未被引用到作物區域試驗資料之穩定性分析。為尋求適當可行的方法,對作物區域試驗資料作一鑑定與判斷,以找出有影響力的離群值,本研究利用Yates and Cochran(1938)之大麥資料作為材料,進行各種離群值診斷法在穩定性分析的應用分析。結果得知,以LS殘差為基礎的傳統迴歸診斷法並不適合作為離群診斷工具,而利用穩健迴歸可有效地辨識出資料的型式及偵測出離群值。 |
英文摘要 | Linear regression analysis is commonly used to assess the relative stability of varieties grown at different regions in Taiwan. However, the converntional least squares (LS) regression is susceptible to the occurrence of outliers (or unusual observations), which may have a deleterious effect on estimates of regression coefficients and on homogeneity of residual mean squares from the regression. Thus, outliers may have a significant impact on the precision of stability analysis. Many diagnostic statistics have been designed to detect outliers. They are classified into two approaches: classical regression diagnostics and recently developed robust regression. However, they are never applied in stability analysis of regional trial data. To investigate their applicability, demonstration of several diagnostics for the outlier detection using the barley data of Yates and Cochran (1938) was performed. The results revealed that the residuals from LS fits are not useful as outlier diagnostics, whereas the robust regression is useful in screening data sets and identifying outliers. |
本系統中英文摘要資訊取自各篇刊載內容。