(3.236.122.9) 您好!臺灣時間:2021/05/14 05:13
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:陳慧敏
研究生(外文):Hui-Min Chen
論文名稱:潛在類別羅吉斯迴歸分析
論文名稱(外文):Latent Class Logistic Regression Analysis
指導教授:楊敏生楊敏生引用關係
指導教授(外文):Min-Shen Yang
學位類別:碩士
校院名稱:中原大學
系所名稱:數學研究所
學門:數學及統計學門
學類:數學學類
論文種類:學術論文
論文出版年:2001
畢業學年度:89
語文別:英文
論文頁數:33
中文關鍵詞:潛在類別羅吉斯迴歸模糊類別
外文關鍵詞:logistic regressionfuzzy classlatent class
相關次數:
  • 被引用被引用:0
  • 點閱點閱:224
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0

摘 要
在對群集類別資料作分析時,找尋混合分配的參數估計是一個重要
的步驟。在Yang and Yu (1999)中曾利用最大概似(MLE)演算法,期望最
大概似(EM)演算法,分類最大概似(CML)演算法及模糊分類最大概似
(FCML)演算法估計多變量伯努力混合型的參數。這篇論文主要是將其
中EM, CML 及FCML 三種演算法推展至迴歸分析上以形容解釋變數對
反應變數的影響。此外,我們只著重於探討二元反應變數的資料,而這
也就是潛在類別類別羅吉斯迴歸模型的分析。接著利用電腦生成數值例
子並藉由推導出的演算法對潛在類別羅吉斯迴歸模型做參數估計,並討
論演算法之數值模擬結果的差異性。


Abstract
Mixtures of distributions are used to analyze the grouped categorical data. The
estimation of parameters is an important step for mixture distributions. According to
Yang and Yu (1999), they described maximum likelihood estimation (MLE) algorithm,
expection maximization (EM) algorithm, classification maximum likelihood (CML)
algorithm and fuzzy classification maximum likelihood (FCML) algorithm to estimate
the parameters of a mixture of multivariate Bernoulli distributions. In this paper, we
will extend EM, CML and FCML algorithms to regression analysis to describe the
effects of the explanatory variables on the response variable. This paper focus on
binary responses about the logistic regression analysis with a latent class model. We
then use the extend algorithms to estimate the parameters of the latent class logistic
regression model. The numerical comparisons are also made. Finally, we give
numerical results for these algorithms.


Contents
1. Introduction 1
2. A mixture model of distribution with latent class and fuzzy class 2
3. Logistic regression model 3
4. Latent class logistic regression analysis and its algorithm 4
4.1 A mixture model of logistic regression 5
4.2 Estimation 8
4.2.1 EM algorithm 9
4.2.2 CML algorithm 16
4.2.3 FCML algorithm 21
5. Numerical results 26
6. Conclusions 31
References 32


ReferenceAnderson, T. W. (1954), On estimation of parameters in latent structureanalysis. Psychometrika, 19, 1-10.Agresti, A. (1990), Categorical Data Analysis. New York: Wiley.DeSarbo, W. S., Wedel, M., and Bult, J. R. (1993), A latent class posi-tionregression model for heterogeneous count data. Journal of AppliedEconometrics, 8, 397-411.DeSarbo, W. S. and Wdel, M. (1995), A mixture likelihood approach forgeneralized linear models. Journal of Classification, 12, 21-55.Everitt, B. S. and Hand, D. J. (1981), Finite Mixture Distributions. NewYork: Chapman and Hall.Everitt,B.S. (1984), An Introduction to Latent Variable Models. NewYork: Chapman and Hall.Jobson, J. D. (1992), Applied Multivariate Data Analysis, Vol. 2. Cat-egoricaland Multivariate Methods. New York: Springer-Verlag.Lazarsfeld, P. F. (1950), The logical and mathematical foundation oflatent structure analysis. Psychometrika, 16, 151-166.McCullagh, P. and Nelder, J. A. (1989), Generalized Linear Models. NewYork : Chapman and Hall.McLachlan, G. J. and K. E. Basford (1988), Mixture Models: Inferenceand Aapplications to Clustering. New York: Marcel Dekker.Nelder, J. A. and Wedderburn, R. W. M. (1972), Generalized linearmodels. Journal of the Royal Statistical Society, Series A, 135, 370-384.Yang, M. S. (1993), On a class of fuzzy classification maximum likelihoodprocedures. Fuzzy Sets and Systems, 57, 365-375.Yang, M. S. and Yu, N. Y. (1999), On estimation of parameters in latentclass models using clustering algorithms. (submitted).Zadeh, L. A. (1965), Fuzzy sets. Inform. and control. 8, 338-353.33

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔