Complex models and computational methods in statistics

The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, de...

Ful tanımlama

Kaydedildi:
Detaylı Bibliyografya
Yazar: Grigoletto, Matteo
Diğer Yazarlar: Lisi, Francesco (Yayın yönetmeni), Petrone, Sonia (Yayın yönetmeni)
Materyal Türü: Livre numérique
Dil:Anglais
Baskı/Yayın Bilgisi: Milano : Springer Milan 2013.
Cham : Springer Nature
Seri Bilgileri:Contributions to Statistics
Online Erişim:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Not: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Complex Models and Computational Methods in Statistics, Texte imprimé, 9788847028722
• Complex Models and Computational Methods in Statistics, Texte imprimé, 9788847055650
• Complex models and computational methods in statistics, Matteo Grigoletto, Francesco Lisi, Sonia Petrone, Milan, Springer, Physica-Verlag, 2013, 1 vol. (VIII-227 pages), Contributions to statistics, 978-88-470-2870-8
LEADER 04098nam a22003617a 4500
001 945986
008 130325s2013 xx ||| |||| 00| 0 eng d
009 PPN168334860
020 |a 9788847028715 
041 0 |a eng 
082 |a 519.5 
100 1 |a Grigoletto, Matteo. 
245 1 0 |a Complex models and computational methods in statistics   |c edited by Matteo Grigoletto, Francesco Lisi, Sonia Petrone. 
260 |a Milano :  |b Springer Milan. 
260 |a Cham :  |b Springer Nature,  |c 2013. 
490 0 |a Contributions to Statistics  |x 2628-8966 
500 |a Archives Springer e-books (Licence nationale) 
500 |a Archives Springer e-books (Licence nationale) 
505 0 |a A new unsupervised classification technique through nonlinear non parametric mixed effects models -- Estimation approaches for the apparent diffusion coefficient in Rice-distributed MR signals -- Longitudinal patterns of financial product ownership: a latent growth mixture approach -- Computationally efficient inference procedures for vast dimensional realized covariance models -- A GPU software library for likelihood-based inference of environmental models with large datasets -- Theoretical Regression Trees: a tool for multiple structural-change models analysis -- Some contributions to the theory of conditional Gibbs partitions -- Estimation of traffic matrices for LRD traffic -- A Newton's method for benchmarking time series -- Spatial smoothing for data distributed over non-planar domains -- Volatility swings in the US financial markets -- Semicontinuous regression models with skew distributions -- Classification of multivariate linear-circular data with nonignorable missing values -- Multidimensional connected set detection in clustering based on nonparametric density estimation -- Using integrated nested Laplace approximations for modelling spatial healthcare utilization -- Supply function prediction in electricity auctions -- A hierarchical bayesian model for RNA-Seq data. 
506 |a Accès en ligne pour les établissements français bénéficiaires des licences nationales 
506 |a Accès soumis à abonnement pour tout autre établissement 
506 |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. chttps://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 
520 |a The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems. This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical methods. 
700 1 |a Lisi, Francesco.  |4 pbd 
700 1 |a Petrone, Sonia.  |4 pbd 
776 0 |t Complex Models and Computational Methods in Statistics  |b Texte imprimé  |z 9788847028722 
776 0 |t Complex Models and Computational Methods in Statistics  |b Texte imprimé  |z 9788847055650 
776 0 |0 180571192  |t Complex models and computational methods in statistics  |f Matteo Grigoletto, Francesco Lisi, Sonia Petrone  |c Milan  |n Springer  |n Physica-Verlag  |d 2013  |p 1 vol. (VIII-227 pages)  |s Contributions to statistics  |z 978-88-470-2870-8 
856 4 |q PDF  |u https://doi.org/10.1007/978-88-470-2871-5  |z Accès sur la plateforme de l'éditeur 
856 4 |u https://revue-sommaire.istex.fr/ark:/67375/8Q1-7G843L8Z-6  |z Accès sur la plateforme Istex 
856 4 |5 452349901:747899592  |u https://ezproxy.univ-orleans.fr/login?url=https://dx.doi.org/10.1007/978-88-470-2871-5  |z Accès Université d'Orléans 
856 4 |5 180339901:750912642  |u https://ezproxy.insa-cvl.fr/login?qurl=https://dx.doi.org/10.1007/978-88-470-2871-5  |z Accès INSA CVL 
997 |0 945986  |1 Livre numérique  |a Ressource numérique  |b INSA  |b ENSA  |c 0/Bibliothèque numérique/  |c 1/Bibliothèque numérique/Autre ressource numérique/