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https://ah.lib.nccu.edu.tw/handle/140.119/106389| 題名: | LASSO於羅吉斯迴歸模型之估計的應用 Application of LASSO Estimation of a Logistic Regression Model |
作者: | 鍾其昀 | 貢獻者: | 薛慧敏 鍾其昀 |
關鍵詞: | 最小平方法 最大概似估計 |
日期: | 2017 | 上傳時間: | 8-Feb-2017 | 摘要: | 隨著資料量龐大，解釋變數過多的時代來臨，變數選取將是我們重要的議題。在線性迴歸分析中，傳統採用最小平方法(least square method)來估計模型，然而得到的迴歸係數估計值的偏差雖然比較小，但其變異程度卻較大，且預測得也不夠精準。若是考慮對迴歸係數加入限制式時，則估計量將與原本的最小平方法有何差異，偏差與標準差之間的比較。接著將此估計法應用至羅吉斯迴模型時，利用三筆實際資料，比較與最大概似估計(maximum likelihood estimate，簡稱MLE)法建立的迴歸模型及預測準確率，並於模擬實驗中，以表格及圖型呈現兩方法在估計量上的差異。 | 參考文獻: | 一、英文文獻\n1. Boyd, S. and Vandenberghe, L. (2004), Convex Optimization, Cambridge University Press, 215-244.\n2. Breiman, L. (1995) Better Subset Regression Using the Nonnegative Garrotte, American Statistical Association, 37, 373-384.\n3. Breiman, L. and Spector P. (1992) Submodel Selection and Evaluation in Regression. The X-Random Case,\nInternational Statistical Review, 60, 291-319.\n4. Dalal, N. Triggs, B. (2005) Histograms of Oriented Gradients for Human Detection, http://lear.inrialpes.fr/.\n5. Friedl, I., Tilg, N. (1995) Variance estimates in logistic regression using the bootstrap, Communications in Statistic-Theory and Methods, 24(2), 473-486.\n6. Hoerl, E. and Kennard, R. (1970) Ridge Regression: Biased Estimation for Nonorthogonal Problems, American Statistical Association, 12, 55-67.\n7. Osborne, M., Presnell, B. and Turlach, B. (2000) On the LASSO and its dual, Journal of Computational and Graphical Statistics, 9, 319–337.\n8. Sill, M.,Hielscher, T. A and Becker M. (2014) Extended Inference with Lasso and Elastic-Net Regularized Cox and Generalized Linear Models, Journal of Statistical Software, 62, 1-22.\n9. Tibshirani, R. (1996) Regression Shrinkage and Selection via the Lasso, Journal of the Royal Statistical Society, 58, 267-288.\n10. Zhao, X. (2008) Lasso and Its Applications, University of Minnesota Duluth, 4-17.\n11. Zou, H. and Hastie, T. (2005) Regularization and Variable Selection via the Elastic Net, Journal of the Royal Statistical Society, 67, 301-320.\n\n二、中文文獻\n1. 全民人體力學健康教室，淺談三種脊椎歪斜。\n2. 賈金柱，高等統計選講，高等統計入門分析，2.2 節Duality。 | 描述: | 碩士 國立政治大學 統計學系 103354015 |
資料來源: | http://thesis.lib.nccu.edu.tw/record/#G0103354015 | 資料類型: | thesis |
| Appears in Collections: | 學位論文 |
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| 401501.pdf | 913.08 kB | Adobe PDF2 | View/Open |
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