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Complex data modeling and computationally intensive methods for estimation and prediction

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new development...

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Detalles Bibliográficos
Autores principales: Paganoni, Anna, Secchi, Piercesare
Lenguaje:eng
Publicado: Springer 2015
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-11149-0
http://cds.cern.ch/record/1973514
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author Paganoni, Anna
Secchi, Piercesare
author_facet Paganoni, Anna
Secchi, Piercesare
author_sort Paganoni, Anna
collection CERN
description The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.
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spelling cern-19735142021-04-22T06:59:53Zdoi:10.1007/978-3-319-11149-0http://cds.cern.ch/record/1973514engPaganoni, AnnaSecchi, PiercesareComplex data modeling and computationally intensive methods for estimation and predictionMathematical Physics and MathematicsThe book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.Springeroai:cds.cern.ch:19735142015
spellingShingle Mathematical Physics and Mathematics
Paganoni, Anna
Secchi, Piercesare
Complex data modeling and computationally intensive methods for estimation and prediction
title Complex data modeling and computationally intensive methods for estimation and prediction
title_full Complex data modeling and computationally intensive methods for estimation and prediction
title_fullStr Complex data modeling and computationally intensive methods for estimation and prediction
title_full_unstemmed Complex data modeling and computationally intensive methods for estimation and prediction
title_short Complex data modeling and computationally intensive methods for estimation and prediction
title_sort complex data modeling and computationally intensive methods for estimation and prediction
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-319-11149-0
http://cds.cern.ch/record/1973514
work_keys_str_mv AT paganonianna complexdatamodelingandcomputationallyintensivemethodsforestimationandprediction
AT secchipiercesare complexdatamodelingandcomputationallyintensivemethodsforestimationandprediction