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1.

電子ブック
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1. Functional Approach to Optimal Experimental Design
by Viatcheslav B. Melas
出版情報: New York, NY : Springer Science+Business Media, Inc., 2006
シリーズ名: Lecture Notes in Statistics ; 184
オンライン: http://dx.doi.org/10.1007/0-387-31610-8
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2.

電子ブック
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2. Bayesian Computation with R
by Jim Albert
出版情報: New York, NY : Springer-Verlag New York, 2009
オンライン: http://dx.doi.org/10.1007/978-0-387-92298-0
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3.

電子ブック
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3. Optimization. 2nd ed. 2013
by Kenneth Lange
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Springer Texts in Statistics ; 95
オンライン: http://dx.doi.org/10.1007/978-1-4614-5838-8
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目次情報: 続きを見る
Elementary Optimization
The Seven C’s of Analysis
The Gauge Integral
Differentiation
Karush-Kuhn-Tucker Theory
Convexity
Block Relaxation
The MM Algorithm
The EM Algorithm
Newton’s Method and Scoring
Conjugate Gradient and Quasi-Newton
Analysis of Convergence
Penalty and Barrier Methods
Convex Calculus
Feasibility and Duality
Convex Minimization Algorithms
The Calculus of Variations
Appendix: Mathematical Notes
References
Index
Elementary Optimization
The Seven C’s of Analysis
The Gauge Integral
4.

電子ブック
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4. Advances in Mathematical and Statistical Modeling
edited by Roberto Minguez, Jose-Maria Sarabia, N. Balakrishnan, Barry C. Arnold
出版情報: Boston : Birkhäuser Boston, 2008
シリーズ名: Statistics for Industry and Technology ;
オンライン: http://dx.doi.org/10.1007/978-0-8176-4626-4
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