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130702s2013 sz | s |||| 0|eng d |
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|a 9783319000329
|9 978-3-319-00032-9
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|a 10.1007/978-3-319-00032-9
|2 doi
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|a QA276-280
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|a 519.5
|2 23
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|a Statistical Models for Data Analysis
|h [electronic resource] /
|c edited by Paolo Giudici, Salvatore Ingrassia, Maurizio Vichi.
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|a 1st ed. 2013.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2013.
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|a XV, 419 p. 75 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
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|a text file
|b PDF
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|a Studies in Classification, Data Analysis, and Knowledge Organization,
|x 2198-3321
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|a 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. .
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|a The papers in this book cover issues related to the development of novel statistical models for the analysis of data. They offer solutions for relevant problems in statistical data analysis and contain the explicit derivation of the proposed models as well as their implementation. The book assembles the selected and refereed proceedings of the biannual conference of the Italian Classification and Data Analysis Group (CLADAG), a section of the Italian Statistical Society.
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650 |
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|a Statistics .
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650 |
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|a Data mining.
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650 |
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|a Social sciences-Statistical methods.
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650 |
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|a Educational tests and measurements.
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650 |
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0 |
|a Artificial intelligence.
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650 |
1 |
4 |
|a Statistical Theory and Methods.
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650 |
2 |
4 |
|a Data Mining and Knowledge Discovery.
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650 |
2 |
4 |
|a Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.
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650 |
2 |
4 |
|a Statistics in Business, Management, Economics, Finance, Insurance.
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650 |
2 |
4 |
|a Assessment and Testing.
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650 |
2 |
4 |
|a Artificial Intelligence.
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700 |
1 |
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|a Giudici, Paolo.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a Ingrassia, Salvatore.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a Vichi, Maurizio.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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710 |
2 |
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|a SpringerLink (Online service)
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773 |
0 |
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|t Springer Nature eBook
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776 |
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8 |
|i Printed edition:
|z 9783319000336
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776 |
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8 |
|i Printed edition:
|z 9783319000312
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830 |
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|a Studies in Classification, Data Analysis, and Knowledge Organization,
|x 2198-3321
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856 |
4 |
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|u https://doi.uam.elogim.com/10.1007/978-3-319-00032-9
|z Texto Completo
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912 |
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|a ZDB-2-SMA
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912 |
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|a ZDB-2-SXMS
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950 |
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|a Mathematics and Statistics (SpringerNature-11649)
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950 |
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|a Mathematics and Statistics (R0) (SpringerNature-43713)
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