Statistical Models for Data Analysis
- フォーマット:
- 電子ブック
- 責任表示:
- edited by Paolo Giudici, Salvatore Ingrassia, Maurizio Vichi
- 言語:
- 英語
- 出版情報:
- Heidelberg : Springer International Publishing : Imprint: Springer, 2013
- 形態:
- XV, 419 p. 75 illus : online resource
- 著者名:
- シリーズ名:
- Studies in Classification, Data Analysis, and Knowledge Organization ;
- 目次情報:
-
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 Data stream summarization by histograms clustering Web panel representativeness Nonparametric inference via permutation tests for CUB models - 書誌ID:
- IT00007511
- ISBN:
- 9783319000329 [3319000322]
9783319000312 [3319000314]
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