Non-linear multivariate statistical models for biomedical data 医薬データにおける非線形多変量統計モデルに関する研究
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著者
書誌事項
- タイトル
-
Non-linear multivariate statistical models for biomedical data
- タイトル別名
-
医薬データにおける非線形多変量統計モデルに関する研究
- 著者名
-
越水, 孝
- 著者別名
-
コシミズ, タカシ
- 学位授与大学
-
大阪電気通信大学
- 取得学位
-
博士(工学)
- 学位授与番号
-
甲第11号
- 学位授与年月日
-
1999-03-24
注記・抄録
博士論文
目次
- Table of Contents / p2 (0005.jp2)
- Acknowledgements / p1 (0004.jp2)
- Abstract / p6 (0009.jp2)
- Chapters / p1 (0011.jp2)
- 1.Introduction / p1 (0011.jp2)
- 1.1 Brief Introduction to the Problem / p1 (0011.jp2)
- 1.2 Outline of Linear Statistical Models / p2 (0012.jp2)
- 1.3 Extension of Linear Statistical Models to Non-linear Relationship / p3 (0013.jp2)
- 1.4 Format of Dissertation / p4 (0014.jp2)
- Part 1 ASSOCIATION MODELS FOR ANALYSIS OF CONTINGENCY TABLES / (0015.jp2)
- 2.Analysis of Doubly-Ordered Two-way Contingency Tables / p5 (0016.jp2)
- 2.1 Introduction / p5 (0016.jp2)
- 2.2 Association Models with Cumulative-Odds Ratios / p7 (0018.jp2)
- 2.3 Analysis of Association Patterns / p11 (0022.jp2)
- 2.4 Evaluation of Performance of Methods Based on Cumulative-Odds Ratios and Local-Odds Ratios / p15 (0026.jp2)
- 2.5 Conclusion / p21 (0032.jp2)
- 3.Analysis of Singly-Ordered Two-way Contingency Tables / p22 (0033.jp2)
- 3.1 Introduction / p22 (0033.jp2)
- 3.2 Association Models with Location and Dispersion Scores / p25 (0036.jp2)
- 3.3 Numerical Examples / p27 (0038.jp2)
- 3.4 Monte Carlo Simulation Study / p32 (0043.jp2)
- 3.5 Conclusion / p39 (0050.jp2)
- 4.Models to Establish Non-inferiority in Stratified 2x2 Contingency Tables / p41 (0052.jp2)
- 4.1 Introduction / p41 (0052.jp2)
- 4.2 Test Statistics / p44 (0055.jp2)
- 4.3 Two-stage Test for Non-inferiority / p47 (0058.jp2)
- 4.4 Monte Carlo Simulation Study / p53 (0064.jp2)
- 4.5 Conclusion / p58 (0069.jp2)
- Part 2 NON-LINEAR STATISTICAL MODELS USING FEED-FORWARD NEURAL NETWORKS / (0070.jp2)
- 5.Non-linear Models for Binary Response Variables / p59 (0071.jp2)
- 5.1 Introduction / p59 (0071.jp2)
- 5.2 Arc-sine Transformation and Neural Network Likelihood / p60 (0072.jp2)
- 5.3 Conclusion / p73 (0085.jp2)
- 6.Non-linear Discriminant Analysis / p74 (0086.jp2)
- 6.1 Introduction / p74 (0086.jp2)
- 6.2 Neural Discriminant Analysis / p76 (0088.jp2)
- 6.3 Application / p88 (0100.jp2)
- 6.4 Conclusion / p108 (0120.jp2)
- 7.Model Diagnostics / p109 (0121.jp2)
- 7.1 Introduction / p109 (0121.jp2)
- 7.2 Information Criterion / p111 (0123.jp2)
- 7.3 Error Rates / p113 (0125.jp2)
- 7.4 Residual Analysis / p114 (0126.jp2)
- 7.5 Application / p115 (0127.jp2)
- 7.6 Conclusion / p123 (0135.jp2)
- 8.Conclusion / p124 (0136.jp2)
- 8.1 Summary of Results / p124 (0136.jp2)
- 8.2 Future Directions / p126 (0138.jp2)
- Bibliography / p128 (0140.jp2)
- Author's Publication / p138 (0150.jp2)