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1. Handbook of Partial Least Squares : Concepts, Methods and Applications
edited by Vincenzo Esposito Vinzi, Wynne W. Chin, Jörg Henseler, Huiwen Wang
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2010
シリーズ名: Springer Handbooks of Computational Statistics ;
オンライン: http://dx.doi.org/10.1007/978-3-540-32827-8
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2.

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2. Selected Works of R.M. Dudley
edited by Evarist Giné, Vladimir Koltchinskii, Rimas Norvaisa
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Selected Works in Probability and Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-5821-1
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3. Spectral Analysis of Large Dimensional Random Matrices
by Zhidong Bai, Jack W. Silverstein
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-0661-8
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4.

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4. Regression with Linear Predictors
by Per Kragh Andersen, Lene Theil Skovgaard
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Statistics for Biology and Health ; 0
オンライン: http://dx.doi.org/10.1007/978-1-4419-7170-8
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5.

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5. A SAS/IML Companion for Linear Models
by Jamis J. Perrett
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Statistics and Computing ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-5557-9
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6.

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6. Dependence in Probability and Statistics
edited by Paul Doukhan, Gabriel Lang, Donatas Surgailis, Gilles Teyssière
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2010
シリーズ名: Lecture Notes in Statistics ; 200
オンライン: http://dx.doi.org/10.1007/978-3-642-14104-1
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7. Workshop on Branching Processes and Their Applications
edited by Miguel González Velasco, Inés M. Puerto, Rodrigo Martínez, Manuel Molina, Manuel Mota, Alfonso Ramos
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2010
シリーズ名: Lecture Notes in Statistics ; 197
オンライン: http://dx.doi.org/10.1007/978-3-642-11156-3
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8.

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8. Multivariate Nonparametric Methods with R : An approach based on spatial signs and ranks
by Hannu Oja
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Lecture Notes in Statistics ; 199
オンライン: http://dx.doi.org/10.1007/978-1-4419-0468-3
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9. Copula Theory and Its Applications : Proceedings of the Workshop Held in Warsaw, 25-26 September 2009
edited by Piotr Jaworski, Fabrizio Durante, Wolfgang Karl Härdle, Tomasz Rychlik
出版情報: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010
シリーズ名: Lecture Notes in Statistics ; 198
オンライン: http://dx.doi.org/10.1007/978-3-642-12465-5
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10.

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10. Applied Probability. Second
by Kenneth Lange
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Springer Texts in Statistics ; 0
オンライン: http://dx.doi.org/10.1007/978-1-4419-7165-4
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11. Statistical Analysis of Designed Experiments, Third Edition
by Helge Toutenburg, Shalabh
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Springer Texts in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-1148-3
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12.

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12. Large Sample Techniques for Statistics. 1
by Jiming Jiang
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Springer Texts in Statistics ; 0
オンライン: http://dx.doi.org/10.1007/978-1-4419-6827-2
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13. Mathematical and Statistical Methods for Actuarial Sciences and Finance
edited by Marco Corazza, Claudio Pizzi
出版情報: Milano : Springer-Verlag Milan, 2010
オンライン: http://dx.doi.org/10.1007/978-88-470-1481-7
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14.

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14. Laws of Small Numbers: Extremes and Rare Events
by Michael Falk, Jürg Hüsler, Rolf-Dieter Reiss
出版情報: Basel : Springer Basel AG, 2011
オンライン: http://dx.doi.org/10.1007/978-3-0348-0009-9
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15.

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15. A First Course in Statistics for Signal Analysis
by Wojbor A. Woyczynski
出版情報: Boston : Springer Science+Business Media, LLC, 2011
オンライン: http://dx.doi.org/10.1007/978-0-8176-8101-2
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16.

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16. Advances in Directional and Linear Statistics : A Festschrift for Sreenivasa Rao Jammalamadaka
edited by Martin T. Wells, Ashis SenGupta
出版情報: Heidelberg : Springer-Verlag Berlin Heidelberg, 2011
オンライン: http://dx.doi.org/10.1007/978-3-7908-2628-9
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17.

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17. Modelling Operational Risk Using Bayesian Inference
by Pavel V. Shevchenko
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2011
オンライン: http://dx.doi.org/10.1007/978-3-642-15923-7
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18. International Encyclopedia of Statistical Science
edited by Miodrag Lovric
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2011
オンライン: http://dx.doi.org/10.1007/978-3-642-04898-2
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19. Mathematical and Statistical Models and Methods in Reliability : Applications to Medicine, Finance, and Quality Control
edited by V.V. Rykov, N. Balakrishnan, M.S. Nikulin
出版情報: Boston : Springer Science+Business Media, LLC, 2011
シリーズ名: Statistics for Industry and Technology ;
オンライン: http://dx.doi.org/10.1007/978-0-8176-4971-5
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20.

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20. Time Series Analysis and Its Applications : With R Examples
by Robert H. Shumway, David S. Stoffer
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Springer Texts in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-7865-3
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21.

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21. Inequalities: Theory of Majorization and Its Applications. Second
by Albert W. Marshall, Ingram Olkin, Barry C. Arnold
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-0-387-68276-1
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22.

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22. Dynamic Mixed Models for Familial Longitudinal Data
by Brajendra C. Sutradhar
出版情報: New York, NY : Springer Science + Business Media, LLC, 2011
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-8342-8
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23.

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23. Selected Works of Debabrata Basu. 1
edited by Anirban DasGupta
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Selected Works in Probability and Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-5825-9
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24. Selected Works of Donald L. Burkholder. 1
edited by Burgess Davis, Renming Song
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Selected Works in Probability and Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-7245-3
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25.

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25. Le logiciel R : Maîtriser le langage Effectuer des analyses statistiques
by Pierre Lafaye Micheaux, Rémy Drouilhet, Benoît Liquet
出版情報: Paris : Springer-Verlag France, 2011
シリーズ名: Statistique et probabilités appliquées ;
オンライン: http://dx.doi.org/10.1007/978-2-8178-0115-5
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26. Classification and Multivariate Analysis for Complex Data Structures
edited by Bernard Fichet, Domenico Piccolo, Rosanna Verde, Maurizio Vichi
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2011
シリーズ名: Studies in Classification, Data Analysis, and Knowledge Organization ;
オンライン: http://dx.doi.org/10.1007/978-3-642-13312-1
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27.

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27. Interactive LISREL in Practice : Getting Started with a SIMPLIS Approach
by Armando Luis Vieira
出版情報: Berlin, Heidelberg : Armando Luis Vieira, 2011
シリーズ名: SpringerBriefs in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-3-642-18044-6
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28.

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28. Statistics for Non-Statisticians
by Birger Madsen
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2011
オンライン: http://dx.doi.org/10.1007/978-3-642-17656-2
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29.

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29. An Introduction to Applied Multivariate Analysis with R
by Brian Everitt, Torsten Hothorn
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Use R ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-9650-3
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30.

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30. Probability Inequalities
by Zhengyan Lin, Zhidong Bai
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2011
オンライン: http://dx.doi.org/10.1007/978-3-642-05261-3
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31. Selected Works of Murray Rosenblatt. 1
edited by Richard A. Davis, Keh-Shin Lii, Dimitris N. Politis
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Selected Works in Probability and Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-8339-8
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32.

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32. Probability for Statistics and Machine Learning : Fundamentals and Advanced Topics. 1
by Anirban DasGupta
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Springer Texts in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-9634-3
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33.

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33. Plane Answers to Complex Questions : The Theory of Linear Models. 4
by Ronald Christensen
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Springer Texts in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-9816-3
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34.

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34. Generalized Estimating Equations
by Andreas Ziegler
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Lecture Notes in Statistics ; 204
オンライン: http://dx.doi.org/10.1007/978-1-4614-0499-6
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35. Targeted Learning : Causal Inference for Observational and Experimental Data
by Mark J. van der Laan, Sherri Rose
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-9782-1
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36. New Perspectives in Statistical Modeling and Data Analysis : Proceedings of the 7th Conference of the Classification and Data Analysis Group of the Italian Statistical Society, Catania, September 9 - 11, 2009
edited by Salvatore Ingrassia, Roberto Rocci, Maurizio Vichi
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2011
シリーズ名: Studies in Classification, Data Analysis, and Knowledge Organization ;
オンライン: http://dx.doi.org/10.1007/978-3-642-11363-5
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37.

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37. Fisher, Neyman, and the Creation of Classical Statistics
by Erich L. Lehmann
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
オンライン: http://dx.doi.org/10.1007/978-1-4419-9500-1
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38.

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38. Statistics for High-Dimensional Data : Methods, Theory and Applications
by Peter Bühlmann, Sara van de Geer
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2011
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-3-642-20192-9
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39.

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39. Matrix Tricks for Linear Statistical Models : Our Personal Top Twenty
by Simo Puntanen, George P. H. Styan, Jarkko Isotalo
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2011
オンライン: http://dx.doi.org/10.1007/978-3-642-10473-2
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40.

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40. Régression avec R
by Pierre-André Cornillon, Eric Matzner-Løber
出版情報: Paris : Springer-Verlag France S.A.R.L., 2011
シリーズ名: Collection Pratique R ;
オンライン: http://dx.doi.org/10.1007/978-2-8178-0184-1
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41.

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41. Selected Works of Oded Schramm
edited by Itai Benjamini, Olle Häggström
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Selected Works in Probability and Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-9675-6
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42.

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42. Séries temporelles avec R : Méthodes et cas
by Yves Aragon
出版情報: Paris : Springer Paris, 2011
シリーズ名: Pratique R ; 0
オンライン: http://dx.doi.org/10.1007/978-2-8178-0208-4
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43.

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43. Méthodes de Monte-Carlo avec R
by Christian P. Robert, George Casella
出版情報: Paris : Springer-Verlag France S.A.R.L., 2011
シリーズ名: Collection Pratique R ;
オンライン: http://dx.doi.org/10.1007/978-2-8178-0181-0
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44.

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44. Bayesian Theory and Methods with Applications
by Vladimir Savchuk, Chris P. Tsokos
出版情報: Paris : Atlantis Press, 2011
シリーズ名: Atlantis Studies in Probability and Statistics ; 1
オンライン: http://dx.doi.org/10.2991/978-94-91216-14-5
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45. Analyse statistique des risques agro-environnementaux : Études de cas
by David Makowski, Hervé Monod
出版情報: Paris : Springer Paris, 2011
シリーズ名: Collection Statistique et probabilités appliquées ;
オンライン: http://dx.doi.org/10.1007/978-2-8178-0251-0
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46.

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46. Argomenti di probabilità e statistica
by Rita Giuliano
出版情報: Milano : Springer Milan, 2011
オンライン: http://dx.doi.org/10.1007/978-88-470-1759-7
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47.

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47. Selected Works of Terry Speed
edited by Sandrine Dudoit
出版情報: New York, NY : Springer New York, 2012
シリーズ名: Selected Works in Probability and Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4614-1347-9
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48.

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48. Graphical Models with R
by Søren Højsgaard, David Edwards, Steffen Lauritzen
出版情報: Boston, MA : Springer US, 2012
シリーズ名: Use R! ;
オンライン: http://dx.doi.org/10.1007/978-1-4614-2299-0
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49.

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49. Essentials of Stochastic Processes. 2nd ed. 2012
by Richard Durrett
出版情報: New York, NY : Springer New York, 2012
シリーズ名: Springer Texts in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4614-3615-7
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50.

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50. Inference for Functional Data with Applications
by Lajos Horváth, Piotr Kokoszka
出版情報: New York, NY : Springer New York, 2012
シリーズ名: Springer Series in Statistics ; 200
オンライン: http://dx.doi.org/10.1007/978-1-4614-3655-3
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51.

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51. A Comparison of the Bayesian and Frequentist Approaches to Estimation
by Francisco J. Samaniego
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-5941-6
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52.

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52. mODa 9 – Advances in Model-Oriented Design and Analysis : Proceedings of the 9th International Workshop in Model-Oriented Design and Analysis held in Bertinoro, Italy, June 14-18, 2010
edited by Alessandra Giovagnoli, Anthony C. Atkinson, Bernard Torsney, Caterina May
出版情報: Heidelberg : Springer-Verlag Berlin Heidelberg, 2010
シリーズ名: Contributions to Statistics ;
オンライン: http://dx.doi.org/10.1007/978-3-7908-2410-0
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53.

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53. Theoretical Statistics : Topics for a Core Course
by Robert W. Keener
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Springer Texts in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-0-387-93839-4
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54.

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54. Selected Works of C.C. Heyde
edited by Ross Maller, Ishwar Basawa, Peter Hall, Eugene Seneta
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Selected Works in Probability and Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-5823-5
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55.

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55. Regression : Linear Models in Statistics
by N. H. Bingham, John M. Fry
出版情報: London : Springer-Verlag London Limited, 2010
シリーズ名: Springer Undergraduate Mathematics Series ;
オンライン: http://dx.doi.org/10.1007/978-1-84882-969-5
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56.

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56. Statistique : La théorie et ses applications. Deuxiéme èdition avec exercices corrigè
by Michel Lejeune
出版情報: Paris : Springer-Verlag Paris, 2010
シリーズ名: Statistique et probabilitès appliquèes ; 0
オンライン: http://dx.doi.org/10.1007/978-2-8178-0157-5
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57.

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57. Complex Data Modeling and Computationally Intensive Statistical Methods
edited by Pietro Mantovan, Piercesare Secchi
出版情報: Milano : Springer-Verlag Milan, 2010
シリーズ名: Contributions to Statistics ;
オンライン: http://dx.doi.org/10.1007/978-88-470-1386-5
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58.

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58. Statistical Analysis of Management Data. 2
by Hubert Gatignon
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
オンライン: http://dx.doi.org/10.1007/978-1-4419-1270-1
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59.

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59. The Pleasures of Statistics : The Autobiography of Frederick Mosteller
by Frederick Mosteller ; edited by Stephen E. Fienberg, David C. Hoaglin, Judith M. Tanur
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
オンライン: http://dx.doi.org/10.1007/978-0-387-77956-0
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60.

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60. Exploring Research Frontiers in Contemporary Statistics and Econometrics : A Festschrift for Léopold Simar
edited by Ingrid Van Keilegom, Paul W. Wilson
出版情報: Heidelberg : Physica-Verlag HD, 2012
オンライン: http://dx.doi.org/10.1007/978-3-7908-2349-3
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61.

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61. Regression Analysis Under A Priori Parameter Restrictions
by Pavel S. Knopov, Arnold S. Korkhin
出版情報: New York, NY : Springer Science+Business Media, LLC, 2012
シリーズ名: Springer Optimization and Its Applications ; 54
オンライン: http://dx.doi.org/10.1007/978-1-4614-0574-0
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62.

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62. A Beginner's Guide to Discrete Mathematics. Second Edition
by W.D. Wallis
出版情報: Boston : Springer Science+Business Media, LLC, 2012
オンライン: http://dx.doi.org/10.1007/978-0-8176-8286-6
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63.

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63. Parametric Statistical Change Point Analysis : With Applications to Genetics, Medicine, and Finance. Second Edition
by Jie Chen, Arjun K. Gupta
出版情報: Boston : Birkhäuser Boston, 2012
オンライン: http://dx.doi.org/10.1007/978-0-8176-4801-5
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64.

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64. Competing Risks and Multistate Models with R
by Jan Beyersmann, Arthur Allignol, Martin Schumacher
出版情報: New York, NY : Springer Science+Business Media, LLC, 2012
シリーズ名: Use R! ;
オンライン: http://dx.doi.org/10.1007/978-1-4614-2035-4
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65.

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65. Visualizing Time : Designing Graphical Representations for Statistical Data
by Graham Wills
出版情報: New York, NY : Springer Science+Business Media, LLC, 2012
シリーズ名: Statistics and Computing ;
オンライン: http://dx.doi.org/10.1007/978-0-387-77907-2
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66.

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66. Probability with Statistical Applications
by Rinaldo B. Schinazi
出版情報: Boston : Springer Science+Business Media, LLC, 2012
オンライン: http://dx.doi.org/10.1007/978-0-8176-8250-7
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67.

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67. Modern Mathematical Statistics with Applications. 2
by Jay L. Devore, Kenneth N. Berk
出版情報: New York, NY : Springer Science+Business Media, LLC, 2012
シリーズ名: Springer Texts in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4614-0391-3
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68.

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68. Probability Approximations and Beyond
edited by Andrew Barbour, Hock Peng Chan, David Siegmund
出版情報: New York, NY : Springer Science+Business Media, LLC, 2012
シリーズ名: Lecture Notes in Statistics ; 205
オンライン: http://dx.doi.org/10.1007/978-1-4614-1966-2
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69.

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69. Two-Way Analysis of Variance : Statistical Tests and Graphics Using R
by Thomas W. MacFarland
出版情報: New York, NY : Thomas W. MacFarland, 2012
シリーズ名: SpringerBriefs in Statistics ; 1
オンライン: http://dx.doi.org/10.1007/978-1-4614-2134-4
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70. Selected Works of Willem van Zwet
edited by Sara van de Geer, Marten Wegkamp
出版情報: New York, NY : Springer Science+Business Media, LLC, 2012
シリーズ名: Selected Works in Probability and Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4614-1314-1
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71. Statistical Tools for Measuring Agreement. 1
by Lawrence Lin, A. S. Hedayat, Wenting Wu
出版情報: New York, NY : Springer New York : Imprint: Springer, 2012
オンライン: http://dx.doi.org/10.1007/978-1-4614-0562-7
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Introduction
Continuous Data
Categorical Data
Sample Size and Power
A Unified Model for Coninutous and Categorical Data
A Comparative Model for Continuous and Categorical Data
Workshop
Introduction
Continuous Data
Categorical Data
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72. Selected Works of David Brillinger
edited by Peter Guttorp, David Brillinger
出版情報: New York, NY : Springer New York : Imprint: Springer, 2012
シリーズ名: Selected Works in Probability and Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4614-1344-8
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Part 1: Theoretical Statistics
Part 2. Time Series Papers
Part 3. Population Biology and Environment
Part 4. Point Processes
Part 1: Theoretical Statistics
Part 2. Time Series Papers
Part 3. Population Biology and Environment
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73. Astrostatistics and Data Mining
edited by Luis Manuel Sarro, Laurent Eyer, William O'Mullane, Joris De Ridder
出版情報: New York, NY : Springer New York : Imprint: Springer, 2012
シリーズ名: Springer Series in Astrostatistics ; 2
オンライン: http://dx.doi.org/10.1007/978-1-4614-3323-1
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??? 'Science with Gaia: how will we deal with a complex billion-source  catalogue and data archive?' by Anthony Brown (Leiden University,Netherlads)
'Recent Advances in cosmological Bayesian model comparison' by  Roberto Trotta (University College London, UK)
'The Art of Data Science' by  Matthew Graham (Center for Advanced  Computing Research, California Institute  of Technology, USA)
'Astronomical Surveys: from SDSS to LSST' by Robert Lupton  (Princeton University, USA)
'Exoplanet demography, quasar target selection, and probabilistic  redshift estimation:  Hierarchical models for density estimation,  classification, and regression.' by David Hogg (New York University,  USA)
'Learning to disentangle Exoplanet signals from correlated noise'  by Suzanne Aigrain (Oxford University, UK)
Astroinformatics and data mining: how to cope with the data  tsunami' by Giuseppe Longo (Federico II University, Italy)
Advanced statistical techniques for the processing of astronomical data: time series, images, low number statistics for high energy photons, heteroskedastic data, non-detections
Challenges in the data mining of astronomical databases: the class imbalance in training sets or how to define prior robust preprocessing for supervised/unsupervised classification robust inference with heterogeneous datasets, how to combine observations, models, priors, etc in a training/test set error propagation
The challenge of petabyte size databases: scalability, parallel computing, accuracy
Geometric data organization, sky indexing for efficient data retrieval, intelligent access to petabyte size databases
Knowledge Discovery in astronomical archives: outlier detection, new object types, parametric inference, model fitting and model selection, etc
Combining the classical domain knowledge approach with machine learning techniques
Global approaches for global datasets. The Galaxy zoo and the Universe zoo
The Virtual Observatories, Data Mining and Astrostatistics: software, standards, protocols
??? 'Science with Gaia: how will we deal with a complex billion-source  catalogue and data archive?' by Anthony Brown (Leiden University,Netherlads)
'Recent Advances in cosmological Bayesian model comparison' by  Roberto Trotta (University College London, UK)
'The Art of Data Science' by  Matthew Graham (Center for Advanced  Computing Research, California Institute  of Technology, USA)
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74. Markov Bases in Algebraic Statistics
by Satoshi Aoki, Hisayuki Hara, Akimichi Takemura
出版情報: New York, NY : Springer New York : Imprint: Springer, 2012
シリーズ名: Springer Series in Statistics ; 199
オンライン: http://dx.doi.org/10.1007/978-1-4614-3719-2
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Exact tests for contingency tables and discrete exponential families
Markov chain Monte Carlo methods over discrete sample space
Toric ideals and their Gröbner bases
Definition of Markov bases and other bases
Structure of minimal Markov bases
Method of distance reduction
Symmetry of Markov bases
Decomposable models of contingency tables
Markov basis for no-three-factor interaction models and some other hierarchical models
Two-way tables with structural zeros and fixed subtable sums
Regular factorial designs with discrete response variables
Group-wise selection models
The set of moves connecting specific fibers
Disclosure limitation problem and Markov basis
Gröbner basis techniques for design of experiments
Running Markov chain without Markov bases
References
Index
Exact tests for contingency tables and discrete exponential families
Markov chain Monte Carlo methods over discrete sample space
Toric ideals and their Gröbner bases
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75. Modeling Infectious Disease Parameters Based on Serological and Social Contact Data : A Modern Statistical Perspective
by Niel Hens, Ziv Shkedy, Marc Aerts, Christel Faes, Pierre Van Damme, Philippe Beutels
出版情報: New York, NY : Springer New York : Imprint: Springer, 2012
シリーズ名: Statistics for Biology and Health ; 63
オンライン: http://dx.doi.org/10.1007/978-1-4614-4072-7
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Mathematical models for infectious diesease
The static model
The dynamic model
The stochastic model
Implementation of models in MATLAB
Data sources for modelling infectious diseases
Estimation from serological data
Parametric models for teh prevalence and the force of infection
Non-parametric approaches to model the prevalence and force of infection
Semi-parametric approaches to model the prevalence and force of infection
A Bayesian approach
Modelling the prevalence and the force of infection direction from antibody levels
Modelling multivariate serological data
Estimation from other data sources
Estimating mixing patterns and Ro in a heterogenous population
Modelling in a homogeneous population
Modelling in a heterogeneous population
Modelling AIDS outbreak data
Modelling hepatitis C among injection drug users
Modelling dengue
Modelling bovine herpes virus in cattle
Mathematical models for infectious diesease
The static model
The dynamic model
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76. Modeling Psychophysical Data in R
by Kenneth Knoblauch, Laurence T. Maloney
出版情報: New York, NY : Springer New York : Imprint: Springer, 2012
シリーズ名: Use R! ; 32
オンライン: http://dx.doi.org/10.1007/978-1-4614-4475-6
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A First Tour through R by Example
Modeling in R
Signal Detection Theory (SDT)
The Psychometric Function: Introduction
The Psychometric Function: Continuation
Classification Images
Maximum Likelihood Difference Scaling (MLDS)
Maximum Likelihood Conjoint Measurement (MLCM)
Mixed-Effect Models
Some Basics of R
Statistical Background
References
Index
A First Tour through R by Example
Modeling in R
Signal Detection Theory (SDT)
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77. Restricted Kalman Filtering : Theory, Methods, and Application
by Adrian Pizzinga
出版情報: New York, NY : Springer New York : Imprint: Springer, 2012
シリーズ名: SpringerBriefs in Statistics ; 12
オンライン: http://dx.doi.org/10.1007/978-1-4614-4738-2
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Introduction
Linear state space models and the Kalman filtering: a briefing
Restricted Kalman filtering: theoretical issues
Restricted Kalman filtering: methodological issues
Applications
Further Extensions
Introduction
Linear state space models and the Kalman filtering: a briefing
Restricted Kalman filtering: theoretical issues
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78. Handbook of Computational Statistics : Concepts and Methods. 2nd ed. 2012. revised and updated
edited by James E. Gentle, Wolfgang Karl Härdle, Yuichi Mori
出版情報: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012
シリーズ名: Springer Handbooks of Computational Statistics ;
オンライン: http://dx.doi.org/10.1007/978-3-642-21551-3
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Part I  Computational Statistics
Part II  Statistical Computing
Part III  Statistical Methodology
Part IV  Selected Applications
Part I  Computational Statistics
Part II  Statistical Computing
Part III  Statistical Methodology
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79. Frontiers in Statistical Quality Control 10
edited by Hans-Joachim Lenz, Wolfgang Schmid, Peter-Theodor Wilrich
出版情報: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2012
シリーズ名: Frontiers in Statistical Quality Control ; 10
オンライン: http://dx.doi.org/10.1007/978-3-7908-2846-7
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Part I On-line Control
A GLR Control Chart for Monitoring the Process Variance by Marion R. Reynolds, Jr., and Jianying Lou
On the Robustness of the Shewhart Control Chart to Diffrent Types of Dependencies in Data by Olgierd
Assessing the Impact of Autocorrelation in Misleading Signals in Simultaneous Residual Schemes for the Process Mean and Variance: a Stochastic Ordering Approach by Patricia Ferreira Ramos, Manuel Cabral Morais, Antonio Pacheco and Wolfgang Schmid
More on Control Charting under Drift by Sven Knoth
Limit Properties of EWMA Charts for Stationary Processes by Manuel Cabral Morais, Yarema Okhrin, and Wolfgang Schmid
Economic Control Chart Policies for Monitoring Variables when there are Two Components of Variance by Erwin Saniga, James Lucas, Darwin Davis, and Thomas McWilliams
Process Monitoring Using an Online Nonlinear Data Reduction Based Control Chart by Issam Ben Khediri and Claus Weihs
On the Integration of SPC and APC: APC can be a Convenient Support for SPC by Ken Nishina, Masanobu Higashide, Hironobu Kawamura, and Naru Ishii
Process Adjustment Control Chart for Simultaneous Monitoring of Process Capability and State of Statistical Control by Hironobu Kawamura, Ken Nishina and Tomomichi Suzuki
Adaptive Threshold Methods for Monitoring Rates in Public Health Surveillance by Linmin Gan, William H. Woodall, and John L. Szarka
Spatiotemporal Bio Surveillance Under Non-homogeneous Population by Sung Won Han, Wei Jiang, and Kwok-Leung Tsui
Monitoring Hospital-Associated Infections with Control Charts by Christina M. Mastrangelo and Anna M. Gillan
Design and Implementation of Systems for Monitoring Lifetime Data  by Emmanuel Yashchin
A Robust Detection Procedure for Multiple Change Points of Linear Trends by Seiichi Yasui, Hidehisa Noguchi and Yoshikazu Ojima
Risk-adjusted Cumulative Sum Charting Procedures by Fah F. Gan, Lin Lin, and Chok K. Loke
Bayesian Sampling Plans for Inspection by Variables by Peter-Th. Wilrich
Quality Assessment in the Presence of Additional Data in Photovoltaics by Sabine Meisen, Andrey Pepelyshev and Ansgar Steland
On Practical Uses of ISO Standards - Two Case Studies by Jürgen Iwersen
Part II Off-line Control: Hybrid Space-Filling Designs for Computer Experiments by Rachel T. Johnson, Douglas C. Montgomery and Kathryn S. Kennedy
Optimal Design for Multifactor Life Testing Experiments for Exponentially Distributed Lifetimes by Brandon R. Englert, Steven E. Rigdon, Connie M. Borror, Douglas C. Montgomery and Rong Pan
Accelerated Lifetime Testing of Thermal Insulation Elements by Rainer Göb, Kristina Lurz, and Ulrich Heinemann
Proposal of Advanced Taguchi's Linear Graphs for Split-Plot Experiments by Tomomichi Suzuki, Hironobu Kawamura, Seiichi Yasui and Yoshikazu Ojima
A Practical Variable Selection for Linear Models by Hidehisa Noguchi, Yoshikazu Ojima, and Seiichi Yasui
Capability of Detection for Poisson Distributed Measurements by Normal Approximations by Yusuke Tsutsumi, Hironobu Kawamura, and Tomomichi Suzuki
Business Data Quality Control - a Step by Step Procedure by Hans-J. Lenz and Esther Borowski
Data Quality: Algorithms for Automatic Detection of Unusual Measurements by Ross Sparks and Chris OkuGami
Uncertainty and Quality Control by Elart von Collani
Part I On-line Control
A GLR Control Chart for Monitoring the Process Variance by Marion R. Reynolds, Jr., and Jianying Lou
On the Robustness of the Shewhart Control Chart to Diffrent Types of Dependencies in Data by Olgierd
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80. Multiple Decrement Models in Insurance : An Introduction Using R
by Shailaja Deshmukh
出版情報: India : Springer India : Imprint: Springer, 2012
オンライン: http://dx.doi.org/10.1007/978-81-322-0659-0
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Multiple Decrement Models
Introduction
Time to Decrement and Cause of Decrement Random Variables
Multiple Decrement Table
Associated Single Decrement Model
Exercises
Premiums and Reserves for Multiple Decrement Model
Actuarial Present Value of Benefit
Computation of Premiums
Computation of Reserves
Defined Benefit Pension Plan
Actuarial Present Value of Pension Benefit
Pension Funding
Accrued Benefit Cost Method for an Individual
Accrued Benefit Cost Method for a Group
Aggregate Actuarial Cost Method
Multi-State Transition Models For Cash Flows
Markov Chain
Actuarial Present Values of Cash Flows
Markov Process Model
Exercises.
Multiple Decrement Models
Introduction
Time to Decrement and Cause of Decrement Random Variables
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81. The Borel-Cantelli Lemma
by Tapas Kumar Chandra
出版情報: India : Springer India : Imprint: Springer, 2012
シリーズ名: SpringerBriefs in Statistics ; 2
オンライン: http://dx.doi.org/10.1007/978-81-322-0677-4
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1. Introductory Chapter
2. Extensions of the First Borel-Cantelli Lemma
3. Variants of the Second Borel-Cantelli Lemma
4. A Strengthened Form of the Second Borel-Cantelli Lemma
5. Conditional Borel-Cantelli Lemmas
6. Miscellaneous Results
1. Introductory Chapter
2. Extensions of the First Borel-Cantelli Lemma
3. Variants of the Second Borel-Cantelli Lemma
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82. Campionamento da popolazioni finite : Il disegno campionario
by Pier Luigi Conti, Daniela Marella
出版情報: Milano : Springer Milan : Imprint: Springer, 2012
シリーズ名: Unitext ;
オンライン: http://dx.doi.org/10.1007/978-88-470-2577-6
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83. Bayesian and Frequentist Regression Methods
by Jon Wakefield
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-0925-1
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Introduction
Frequentist Inference
Bayesian Inference
Linear Models
Binary Data Models
General Regression Models
Introduction
Frequentist Inference
Bayesian Inference
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84. Astrostatistical Challenges for the New Astronomy
edited by Joseph M. Hilbe
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Springer Series in Astrostatistics ; 1
オンライン: http://dx.doi.org/10.1007/978-1-4614-3508-2
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Joseph Hilbe, Jet Propulsion Laboratory and Arizona State University, Astrostatistics: A brief history and view to the future
Thomas Loredo, Cornell Univ, Bayesian astrostatistics: A backward look to the future
Stefano Andreon, INAF-Osservatorio Astronomico di Brera, Italy, Understanding better (some) astronomical data using Bayesian methods
Martin Kunz, Institute for Theoretical Physics, Univ of Geneva, BEAMS: separating the wheat from the chaff in supernova analysis
Benjamin Wandelt, Institut d'Astrophysique de Paris, Université Pierre et Marie Curie, France, Cosmostatistics
Roberto Trotta, Astrophysics Group, Dept of Physics, Imperial College London  (with Farhan Feroz (Cambridge), Mike Hobson (Cambridge), and Roberto Ruiz de Austri (Univ of Valencia, Spain), Recent advances in Bayesian inference in cosmology and astroparticle physics thanks to the Multinest Algorithm
Phillip Gregory, Department of Astronomy, Univ of British Columbia, Canada, Extrasolar planets via Bayesian model fitting
Marc Henrion, Dept of Mathematics, Imperial College, London, UK (with Daniel Mortlock (Imperial), Axel Gandy (Imperial), and David J. Hand (Imperial)), Subspace methods for anomaly detection in high dimensional astronomical databases
Asis Kumar Chattopadhyay, Dept of Statistics, Univ of Calcutta, India (with Tanuka Chattyopadhyay, Tuli De, and Saptarshi Mondal), Independent Component Analysis for dimension reduction classification: Hough transform and CASH Algorithm
Marisa March, Astrophysics Group, Dept of Physics, Imperial College London (with Roberto Trotta), Improved cosmological constraints from a Bayesian hierarchical model of supernova type Ia data
Joseph Hilbe, Jet Propulsion Laboratory and Arizona State University, Astrostatistics: A brief history and view to the future
Thomas Loredo, Cornell Univ, Bayesian astrostatistics: A backward look to the future
Stefano Andreon, INAF-Osservatorio Astronomico di Brera, Italy, Understanding better (some) astronomical data using Bayesian methods
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85. Linear Mixed-Effects Models Using R : A Step-by-Step Approach
by Andrzej Gałecki, Tomasz Burzykowski
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Springer Texts in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4614-3900-4
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Introduction
Linear Models for Independent Observations
Linear Fixed-effects Models for Correlated Data
Linear Mixed-effects Models
Introduction
Linear Models for Independent Observations
Linear Fixed-effects Models for Correlated Data
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86. Probability: A Graduate Course : A Graduate Course. 2nd ed. 2013
by Allan Gut
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Springer Texts in Statistics ; 75
オンライン: http://dx.doi.org/10.1007/978-1-4614-4708-5
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Preface to the First Edition
Preface to the Second Edition
Outline of Contents
Notation and Symbols
Introductory Measure Theory
Random Variables
Inequalities
Characteristic Functions
Convergence
The Law of Large Numbers
The Central Limit Theorem
The Law of the Iterated Logarithm
Limited Theorems
Martingales
Some Useful Mathematics
References
Index
Preface to the First Edition
Preface to the Second Edition
Outline of Contents
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87. The Gini Methodology : A Primer on a Statistical Methodology
by Shlomo Yitzhaki, Edna Schechtman
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Springer Series in Statistics ; 272
オンライン: http://dx.doi.org/10.1007/978-1-4614-4720-7
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Introduction
More Than a Dozen Alternative Ways of Spelling Gini
The Gini equivalents of the covariance, the correlation and the regression coefficient
Decompositions of the GMD
The Lorenz curve and the concentration curve
The extended Gini family of measures
Gini Simple Regressions
Multiple Regressions
Inference on Gini-based parameters -estimation
Inference on Gini-based parameters -testing
Inference on Lorenz and on Concentration curves
Introduction to applications
Social welfare, relative deprivation and the Gini coefficient
Policy Analysis.-  Policy Analysis Using the Decomposition of the Gini by non-marginal analysis.- Incorporating poverty in Policy Analysis - the Marginal Analysis case
Introduction to applications of the GMD and the Lorenz curve in finance
The mean-Gini portfolio and the pricing of capital assets
Applications of Gini methodology in regression analysis
Gini's multiple regressions: two approaches and their interaction
Mixed OLS, Gini and extended Gini regressions.-  An application in statistics - ANOGI
Suggestions for further research
Introduction
More Than a Dozen Alternative Ways of Spelling Gini
The Gini equivalents of the covariance, the correlation and the regression coefficient
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88. Essential Statistical Inference : Theory and Methods
by Dennis D. Boos, L. A. Stefanski
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Springer Texts in Statistics ; 120
オンライン: http://dx.doi.org/10.1007/978-1-4614-4818-1
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目次情報:
Roles of Modeling in Statistical Inference.- Likelihood Construction and Estimation.- Likelihood-Based Tests and Confidence Regions.- Bayesian Inference.- Large Sample Theory: The Basics.- Large Sample Results for Likelihood-Based Methods.- M-Estimation (Estimating Equations).- Hypothesis Tests under Misspecification and Relaxed Assumptions .- Monte Carlo Simulation Studies .- Jackknife.- Bootstrap.- Permutation and Rank Tests.- Appendix: Derivative Notation and Formulas.- References.- Author Index.- Example Index
R-code Index
Subject Index.
Roles of Modeling in Statistical Inference.- Likelihood Construction and Estimation.- Likelihood-Based Tests and Confidence Regions.- Bayesian Inference.- Large Sample Theory: The Basics.- Large Sample Results for Likelihood-Based Methods.- M-Estimation (Estimating Equations).- Hypothesis Tests under Misspecification and Relaxed Assumptions .- Monte Carlo Simulation Studies .- Jackknife.- Bootstrap.- Permutation and Rank Tests.- Appendix: Derivative Notation and Formulas.- References.- Author Index.- Example Index
R-code Index
Subject Index.
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89. The Methods of Distances in the Theory of Probability and Statistics
by Svetlozar T. Rachev, Lev B. Klebanov, Stoyan V. Stoyanov, Frank Fabozzi
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
オンライン: http://dx.doi.org/10.1007/978-1-4614-4869-3
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Main directions in the theory of probability metrics
Probability distances and probability metrics: Definitions
Primary, simple and compound probability distances, and minimal and maximal distances and norms
A structural classification of probability distances.-Monge-Kantorovich mass transference problem, minimal distances and minimal norms
Quantitative relationships between minimal distances and minimal norms
K-Minimal metrics
Relations between minimal and maximal distances
Moment problems related to the theory of probability metrics: Relations between compound and primary distances
Moment distances
Uniformity in weak and vague convergence
Glivenko-Cantelli theorem and Bernstein-Kantorovich invariance principle
Stability of queueing systems.-Optimal quality usage
Ideal metrics with respect to summation scheme for i.i.d. random variables
Ideal metrics and rate of convergence in the CLT for random motions
Applications of ideal metrics for sums of i.i.d. random variables to the problems of stability and approximation in risk theory
How close are the individual and collective models in risk theory?- Ideal metric with respect to maxima scheme of i.i.d. random elements
Ideal metrics and stability of characterizations of probability distributions
Positive and negative de nite kernels and their properties
Negative definite kernels and metrics: Recovering measures from potential
Statistical estimates obtained by the minimal distances method
Some statistical tests based on N-distances
Distances defined by zonoids
N-distance tests of uniformity on the hypersphere.-
Main directions in the theory of probability metrics
Probability distances and probability metrics: Definitions
Primary, simple and compound probability distances, and minimal and maximal distances and norms
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90. Linear-Quadratic Controls in Risk-Averse Decision Making : Performance-Measure Statistics and Control Decision Optimization
by Khanh D. Pham
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: SpringerBriefs in Optimization ;
オンライン: http://dx.doi.org/10.1007/978-1-4614-5079-5
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91. Smoothing Spline ANOVA Models. 2nd ed. 2013
by Chong Gu
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Springer Series in Statistics ; 297
オンライン: http://dx.doi.org/10.1007/978-1-4614-5369-7
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Introduction
Model Construction
Regression with Gaussian-Type Responses
More Splines
Regression and Exponential Families
Regression with Correlated Responses
Probability Density Estimation
Hazard Rate Estimation
Asymptotic Convergence
Penalized Pseudo Likelihood
Introduction
Model Construction
Regression with Gaussian-Type Responses
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92. Selected Works of Peter J. Bickel
edited by Jianqing Fan, Ya'acov Ritov, C.F. Jeff Wu
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Selected Works in Probability and Statistics ; 13
オンライン: http://dx.doi.org/10.1007/978-1-4614-5544-8
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Foreword by Peter J. Bickel
Preface
Biography
Publications
Ph.D. Students
Photos
Rank-Based Nonparametrics
Robust Statistics
Asymptotic Theory
Functional Estimation
Adaptive Estimation
Bootstrap Resampling
High-Dimensional Statistics
Miscellaneous
Foreword by Peter J. Bickel
Preface
Biography
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93. Dihedral Fourier Analysis : Data-analytic Aspects and Applications
by Marlos A. G. Viana, Vasudevan Lakshminarayanan
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
オンライン: http://dx.doi.org/10.1007/978-1-4614-5562-2
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Symmetry and Experimental Data
Algebraic and Data-Analytic Aspects
Curvature and Refraction Data
Symbolic Sequences
Symmetry Preference and Perception
Other Applications
Glossary
Index
Symmetry and Experimental Data
Algebraic and Data-Analytic Aspects
Curvature and Refraction Data
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94. Applied Bayesian Statistics : With R and OpenBUGS Examples
by Mary Kathryn Cowles
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Springer Texts in Statistics ; 98
オンライン: http://dx.doi.org/10.1007/978-1-4614-5696-4
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目次情報: 続きを見る
What is Bayesian statistics?
Review of probability
Introduction to one-parameter models
Inference for a population proportion
Special considerations in Bayesian inference
Other one-parameter models and their conjugate priors
More realism please: Introduction to multiparameter models
Fitting more complex Bayesian models: Markov chain Monte Carlo
Hierarchical models, and more on convergence assessment
Regression and hierarchical regression models
Model Comparison, Model Checking, and Hypothesis Testing
References
Index
What is Bayesian statistics?
Review of probability
Introduction to one-parameter models
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95. OpenStat Reference Manual
by William Miller
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
オンライン: http://dx.doi.org/10.1007/978-1-4614-5740-4
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目次情報:
OPENSTAT REFERENCE MANUAL.- PREFACE.- TABLE OF CONTENTS
INTRODUCTION.- INSTALLING OPENSTAT.- STARTING OPENSTAT.- FILES.- CREATING A FILE.- ENTERING DATA.- SAVING A FILE.- DISTRIBUTIONS.- DESCRIPTIVE ANALYSES.- VERSUS Y PLOTS.- VERSUS MULTIPLE Y PLOT.- CORRELATION.- COMPARISONS.- MULTIVARIATE.- NON-PARAMETRIC.- MEASUREMENT.- STATISTICAL PROCESS CONTROL .- LINEAR PROGRAMMING.- THE ITEM BANKING PROGRAM.- NEURAL NETWORKS.- USING THE PROGRAM.- EXAMPLES
INDEX
OPENSTAT REFERENCE MANUAL.- PREFACE.- TABLE OF CONTENTS
INTRODUCTION.- INSTALLING OPENSTAT.- STARTING OPENSTAT.- FILES.- CREATING A FILE.- ENTERING DATA.- SAVING A FILE.- DISTRIBUTIONS.- DESCRIPTIVE ANALYSES.- VERSUS Y PLOTS.- VERSUS MULTIPLE Y PLOT.- CORRELATION.- COMPARISONS.- MULTIVARIATE.- NON-PARAMETRIC.- MEASUREMENT.- STATISTICAL PROCESS CONTROL .- LINEAR PROGRAMMING.- THE ITEM BANKING PROGRAM.- NEURAL NETWORKS.- USING THE PROGRAM.- EXAMPLES
INDEX
96.

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96. Statistics and Measurement Concepts with OpenStat
by William Miller
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
オンライン: http://dx.doi.org/10.1007/978-1-4614-5743-5
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97.

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97. 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
98.

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98. Essentials of Monte Carlo Simulation : Statistical Methods for Building Simulation Models
by Nick T. Thomopoulos
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
オンライン: http://dx.doi.org/10.1007/978-1-4614-6022-0
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99. Strategic Economic Decision-Making : Using Bayesian Belief Networks to Solve Complex Problems
by Jeff Grover
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: SpringerBriefs in Statistics ; 9
オンライン: http://dx.doi.org/10.1007/978-1-4614-6040-4
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目次情報: 続きを見る
Strategic Economic Decision Making: The Use of Bayesian Belief Networks (BBN) in Solving Complex Problems
A Literature Review of Bayes’ Theorem and Bayesian Belief Networks (BBN)
Statistical Properties of Bayes’ Theorem
Bayes Belief Networks (BBN) Experimental Protocol
Manufacturing Example
Political Science Example
Gambling Example
Publicly Traded Company Default Example
Insurance Risk Levels Example
Acts of Terrorism Example
Currency Wars Example
College Entrance Exams Example
Special Forces Assessment and Selection (SFAS) One-Stage Example
Special Forces Assessment and Selection (SFAS) Two-Stage Example
Strategic Economic Decision Making: The Use of Bayesian Belief Networks (BBN) in Solving Complex Problems
A Literature Review of Bayes’ Theorem and Bayesian Belief Networks (BBN)
Statistical Properties of Bayes’ Theorem
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100. Sequential Experimentation in Clinical Trials : Design and Analysis
by Jay Bartroff, Tze Leung Lai, Mei-Chiung Shih
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Springer Series in Statistics ; 298
オンライン: http://dx.doi.org/10.1007/978-1-4614-6114-2
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目次情報: 続きを見る
Introduction
Nonlinear Regression, Experimental Design, and Phase I Clinical Trials
Sequential Testing Theory and Stochastic Optimization over Time
Group Sequential Design of Phase II and III Trials
Sequential Methods for Vaccine Safety Evaluation and Surveillance in Public Health
Time-Sequential Design of Clinical Trials with Failure-Time Endpoints
Confidence Intervals and p-Values
Adaptive Design of Confirmatory Trials
References
Introduction
Nonlinear Regression, Experimental Design, and Phase I Clinical Trials
Sequential Testing Theory and Stochastic Optimization over Time