頁籤選單縮合
題 名 | 利用極大熵理論對隨機樣本適合度測試之分析=Testing Goodness of Fit for Random Samples Using the Maximum Entropy Theory |
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作 者 | 潘浙楠; 陳光澄; | 書刊名 | 中國統計學報 |
卷 期 | 34:2 1996.06[民85.06] |
頁 次 | 頁194-213 |
分類號 | 319.56 |
關鍵詞 | 關鍵品質特性; 製程能力分析; 極大熵理論; 卡方檢定; K-S檢定; Key quality characteristics; Process capability analysis; Testing goodness of fit; Maximum entropy theorem; Chi-square test; K-S test; |
語 文 | 中文(Chinese) |
中文摘要 | 在品質管制的製程能力分析上,決定關鍵品質特性量測值之機率分配是其中的重要環節,而在可靠度工程的領域中,機率模式的建立則有助於對產品或系統可靠度作正確之預估。因此在檢定何種機率模式較能適切的描述產品之品質特性或壽命分佈函數時,隨機樣本適合度之測試扮演著相當重要的角色。一般常用來考量隨機樣本適合度的檢定有卡方檢定、K-S (Kolomogorov-Smirnov) 檢定等。本文嘗試在隨機樣本分群的情況下,利用極大熵理論對其適合度測試問題作一合理的評估與分析,並與卡方檢定及K-S檢定作進一步比較。最後,以一個繼電器允收測試之實例對上述隨機樣本適合度測試的方法作一驗證與說明。 |
英文摘要 | In process capability studies, one of the decision factors is to determine an adequate distribution for the measurements of key. quality characteristics. In the field of reliability engineering, the probabilistic model building is beneficial to predict product or system reliability. Therefore, in order to select a probability distribution which can best describe the quality characteristic or life span of a product, testing goodness of fit for random samples plays a very important role. Usually, the chi-square and the Kolmogorov-Smirnov test are used. This paper attempts to evaluate and analyze the goodness of fit testing for random samples using the Maximum Entropy Principle (MEP). A comparison among chi-square, K-S, and MEP has also been made. Finally, this paper demonstrates the application of “testing goodness of fit for random samples using MEP” with real data in relay manufacturing. |
本系統中英文摘要資訊取自各篇刊載內容。