Vai al contenuto principale della pagina

Advances in Complex Data Modeling and Computational Methods in Statistics [[electronic resource] /] / edited by Anna Maria Paganoni, Piercesare Secchi



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Titolo: Advances in Complex Data Modeling and Computational Methods in Statistics [[electronic resource] /] / edited by Anna Maria Paganoni, Piercesare Secchi Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Edizione: 1st ed. 2015.
Descrizione fisica: 1 online resource (210 p.)
Disciplina: 005.1
519
519.5
570.15195
620
Soggetto topico: Statistics 
Applied mathematics
Engineering mathematics
Biostatistics
Computational complexity
Software engineering
Statistical Theory and Methods
Applications of Mathematics
Complexity
Software Engineering/Programming and Operating Systems
Persona (resp. second.): PaganoniAnna Maria
SecchiPiercesare
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: 1 Antonino Abbruzzo, Angelo M. Mineo: Inferring networks from high-dimensional data with mixed variables -- 2 Federico Andreis, Fulvia Mecatti: Rounding Non-integer Weights in Bootstrapping Non-iid Samples: actual problem or harmless practice? -- 3 Marika Arena, Giovanni Azzone, Antonio Conte, Piercesare Secchi, Simone Vantini: Measuring downsize reputational risk in the Oil & Gas industry -- 4 Laura Azzimonti, Marzia A. Cremona, Andrea Ghiglietti, Francesca Ieva, Alessandra Menafoglio, Alessia Pini, Paolo Zanini: BARCAMP Technology Foresight and Statistics for the Future -- 5 Francesca Chiaromonte, Kateryna D. Makova: Using statistics to shed light on the dynamics of the human genome: A review -- 6 Nader Ebrahimi, Ehsan S. Soofi and Refik Soyer: Information Theory and Bayesian Reliability Analysis: Recent Advances -- 7 Stephan F. Huckemann: (Semi-) Intrinsic Statistical Analysis on non-Euclidean Spaces -- 8 John T. Kent: An investigation of projective shape space -- 9 Fabio Manfredini, Paola Pucci, Piercesare Secchi, Paolo Tagliolato, Simone Vantini, Valeria Vitelli: Treelet Decomposition of Mobile Phone Data for Deriving City Usage and Mobility Pattern in the Milan Urban Region -- 10 Cristina Mazzali, Mauro Maistriello, Francesca Ieva, Pietro Barbieri: Methodological issues in the use of administrative databases to study heart failure -- 11 Andrea Mercatant: Bayesian inference for randomized experiments with noncompliance and nonignorable missing data -- 12 Antonio Pulcini, Brunero Liseo: Approximate Bayesian Quantile Regression for Panel Data -- 13 Laura M. Sangalli: Estimating surfaces and spatial fields via regression models with differential regularization.  .
Sommario/riassunto: 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.
Titolo autorizzato: Advances in Complex Data Modeling and Computational Methods in Statistics  Visualizza cluster
ISBN: 3-319-11149-3
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910299763803321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: Contributions to Statistics, . 1431-1968