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1. Statistical Analysis of Network Data : Methods and Models
by Eric D. Kolaczyk
出版情報: New York, NY : Springer-Verlag New York, 2009
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-0-387-88146-1
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2. A First Course in Bayesian Statistical Methods
by Peter D. Hoff
出版情報: New York, NY : Springer-Verlag New York, 2009
シリーズ名: Springer Texts in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-0-387-92407-6
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3. Principles and Theory for Data Mining and Machine Learning
by Bertrand Clarke, Ernest Fokoue, Hao Helen Zhang
出版情報: New York, NY : Springer-Verlag New York, 2009
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-0-387-98135-2
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4.

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4. The Elements of Statistical Learning : Data Mining, Inference, and Prediction
by Jerome Friedman, Robert Tibshirani, Trevor Hastie
出版情報: New York, NY : Springer-Verlag New York, 2009
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/b94608
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5.

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5. 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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6.

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6. Classification and Data Mining
edited by Antonio Giusti, Gunter Ritter, Maurizio Vichi
出版情報: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013
シリーズ名: Studies in Classification, Data Analysis, and Knowledge Organization ;
オンライン: http://dx.doi.org/10.1007/978-3-642-28894-4
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目次情報:
Classification and Data Analysis
Data Mining
Applications
Classification and Data Analysis
Data Mining
Applications
7.

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7. Statistical Models for Data Analysis
edited by Paolo Giudici, Salvatore Ingrassia, Maurizio Vichi
出版情報: Heidelberg : Springer International Publishing : Imprint: Springer, 2013
シリーズ名: Studies in Classification, Data Analysis, and Knowledge Organization ;
オンライン: http://dx.doi.org/10.1007/978-3-319-00032-9
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目次情報: 続きを見る
From the contents: Ordering curves by data depth
May the students' career performance helpful in predicting an increase in universities income?
Model-based classification via patterned covariance analysis
Data stream summarization by histograms clustering
Web panel representativeness
Nonparametric inference via permutation tests for CUB models
Asymmetric multidimensional scaling models for seriations
An approach to ranking the hedge funds industry
Correction of incoherences in statistical matching
The analysis of network additionality in the context of territorial innovation policy
Clustering and registration of multidimensional functional data
Classifying tourism destinations
On two classes of weighted rank correlation measures deriving from teh Spearman's r
Beanplot data analysis in a temporal framework
Supervised classification of facial expressions
Grouping around different dimensional affine subspaces
Hospital clustering in the treatment of acute myocardial infarction patients via a Bayesian semiparametric approach
A new fuzzy method to classify professional profiles from job announcements
A metric based approach for the Least Square Regression of multivariate model symbolic data
A Gaussian-Von Mises Hidden Markov model for clustering multivariate linear-circular data
And further articles.
From the contents: Ordering curves by data depth
May the students' career performance helpful in predicting an increase in universities income?
Model-based classification via patterned covariance analysis
8.

電子ブック
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8. Statistical Methods for Ranking Data
by Mayer Alvo, Philip L.H. Yu
出版情報: New York, NY : Springer New York : Imprint: Springer, 2014
シリーズ名: Frontiers in Probability and the Statistical Sciences ;
オンライン: http://dx.doi.org/10.1007/978-1-4939-1471-5
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目次情報: 続きを見る
Introduction
Exploratory Analysis of Ranking Data
Correlation Analysis of Paired Ranking Data
Testing for randomness, agreement and interaction
Block Designs
General Theory of Hypothesis Testing
Testing for Ordered Alternatives
Probability Models for Ranking Data
Probit Models for Ranking Data
Decision Tree Models for Ranking Data
Extension of Distance-Based Models for Ranking Data
Appendix A: Ranking Data Sets
Appendix B: Limit Theorems
Appendix C: Review on Decision Trees
Introduction
Exploratory Analysis of Ranking Data
Correlation Analysis of Paired Ranking Data
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9. Multivariate Statistics : Exercises and Solutions. 2nd ed. 2015
by Wolfgang Karl Härdle, Zdeněk Hlávka
出版情報: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2015
オンライン: http://dx.doi.org/10.1007/978-3-642-36005-3
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目次情報: 続きを見る
Part I Descriptive Techniques:  Comparison of Batches
Part II Multivariate Random Variables:  A Short Excursion into Matrix Algebra
Moving to Higher
Multivariate
Theory of the Multinormal
 Theory of Estimation
Part III Multivariate Techniques: Regression Models
Variable Selection
Decomposition of Data Matrices by Factors
Principal Component Analysis
Factor Analysis
Cluster Analysis
Discriminant Analysis
Correspondence Analysis
Canonical Correlation Analysis
Multidimensional Scaling
Conjoint Measurement Analysis
Applications in Finance
Highly Interactive, Computationally Intensive Techniques
Data Sets
References
Index
Part I Descriptive Techniques:  Comparison of Batches
Part II Multivariate Random Variables:  A Short Excursion into Matrix Algebra
Moving to Higher
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10. Advances in Data Analysis : Proceedings of the 30th Annual Conference of the Gesellschaft für Klassifikation e.V., Freie Universität Berlin, March 8–10, 2006
edited by Reinhold Decker, Hans -J. Lenz
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2007
シリーズ名: Studies in Classification, Data Analysis, and Knowledge Organization ;
オンライン: http://dx.doi.org/10.1007/978-3-540-70981-7
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