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Contemporary Experimental Design, Multivariate Analysis and Data Mining : Festschrift in Honour of Professor Kai-Tai Fang / Jianqing Fan, Jianxin Pan editors
| Contemporary Experimental Design, Multivariate Analysis and Data Mining : Festschrift in Honour of Professor Kai-Tai Fang / Jianqing Fan, Jianxin Pan editors |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xvii, 386 p. : ill. ; 24 cm |
| Soggetto topico |
62H12 - Estimation in multivariate analysis [MSC 2020]
00B30 - Festschriften [MSC 2020] 62-XX - Statistics [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] |
| Soggetto non controllato |
Big Data
Composite design Covariance matrix Data Mining Experimental design Functional data High-Dimensional Data Longitudinal data Machine learning Multivariate Data Network data Quantile regression Robust Design Survival data Variable Selection |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0248857 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Contemporary Experimental Design, Multivariate Analysis and Data Mining : Festschrift in Honour of Professor Kai-Tai Fang / Jianqing Fan, Jianxin Pan editors
| Contemporary Experimental Design, Multivariate Analysis and Data Mining : Festschrift in Honour of Professor Kai-Tai Fang / Jianqing Fan, Jianxin Pan editors |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xvii, 386 p. : ill. ; 24 cm |
| Soggetto topico |
00B30 - Festschriften [MSC 2020]
62-XX - Statistics [MSC 2020] 62H12 - Estimation in multivariate analysis [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] |
| Soggetto non controllato |
Big Data
Composite design Covariance matrix Data Mining Experimental design Functional data High-Dimensional Data Longitudinal data Machine Learning Multivariate Data Network data Quantile regression Robust Design Survival data Variable Selection |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00248857 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Functional statistics and applications : selected papers from MICPS-2013 / Elias Ould Saïd, Idir Ouassou, Mustapha Rachdi editors
| Functional statistics and applications : selected papers from MICPS-2013 / Elias Ould Saïd, Idir Ouassou, Mustapha Rachdi editors |
| Pubbl/distr/stampa | [Cham], : Springer, 2015 |
| Descrizione fisica | XII, 164 p. : ill. ; 24 cm |
| Soggetto topico |
60H07 - Stochastic calculus of variations and the Malliavin calculus [MSC 2020]
60H30 - Applications of stochastic analysis (to PDEs, etc.) [MSC 2020] 92B15 - General Biostatistics [MSC 2020] 62G08 - Nonparametric regression and quantile regression [MSC 2020] 62G20 - Asymptotic properties of nonparametric inference [MSC 2020] 60H40 - White noise theory [MSC 2020] |
| Soggetto non controllato |
Blockshrink wavelets
Dynalets Extreme conditional quantiles Functional data Local linear estimator Queueing Theory Robust regression Spherically symmetric distribution |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0113740 |
| [Cham], : Springer, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Functional statistics and applications : selected papers from MICPS-2013 / Elias Ould Saïd, Idir Ouassou, Mustapha Rachdi editors
| Functional statistics and applications : selected papers from MICPS-2013 / Elias Ould Saïd, Idir Ouassou, Mustapha Rachdi editors |
| Pubbl/distr/stampa | [Cham], : Springer, 2015 |
| Descrizione fisica | XII, 164 p. : ill. ; 24 cm |
| Soggetto topico |
60H07 - Stochastic calculus of variations and the Malliavin calculus [MSC 2020]
60H30 - Applications of stochastic analysis (to PDEs, etc.) [MSC 2020] 60H40 - White noise theory [MSC 2020] 62G08 - Nonparametric regression and quantile regression [MSC 2020] 62G20 - Asymptotic properties of nonparametric inference [MSC 2020] 92B15 - General Biostatistics [MSC 2020] |
| Soggetto non controllato |
Blockshrink wavelets
Dynalets Extreme conditional quantiles Functional data Local linear estimator Queueing Theory Robust regression Spherically symmetric distribution |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | This volume, which highlights recent advances in statistical methodology and applications, is divided into two main parts. The first part presents theoretical results on estimation techniques in functional statistics, while the second examines three key areas of application: estimation problems in queuing theory, an application in signal processing, and the copula approach to epidemiologic modelling. The book’s peer-reviewed contributions are based on papers originally presented at the Marrakesh International Conference on Probability and Statistics held in December 2013. |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00113740 |
| [Cham], : Springer, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
New Frontiers of Biostatistics and Bioinformatics / Yichuan Zhao, Ding-Geng Chen editors
| New Frontiers of Biostatistics and Bioinformatics / Yichuan Zhao, Ding-Geng Chen editors |
| Pubbl/distr/stampa | Cham, : Springer, 2018 |
| Descrizione fisica | xxiv, 463 p. : ill. ; 24 cm |
| Soggetto topico |
92-XX - Biology and other natural sciences [MSC 2020]
92B15 - General Biostatistics [MSC 2020] |
| Soggetto non controllato |
Adaptive Design
Biostatistical Procedures Competing Risk Data Analysis Complex data analysis Data Mining Density Estimation Functional data Gene expression analysis High dimensional statistical method Image Data Analysis Longitudinal data Mixture Model Analysis Multivariate Survival Data Analysis Network analysis Variable Selection Wavelets fMRI data analysis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0124885 |
| Cham, : Springer, 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
New Frontiers of Biostatistics and Bioinformatics / Yichuan Zhao, Ding-Geng Chen editors
| New Frontiers of Biostatistics and Bioinformatics / Yichuan Zhao, Ding-Geng Chen editors |
| Pubbl/distr/stampa | Cham, : Springer, 2018 |
| Descrizione fisica | xxiv, 463 p. : ill. ; 24 cm |
| Soggetto topico |
92-XX - Biology and other natural sciences [MSC 2020]
92B15 - General Biostatistics [MSC 2020] |
| Soggetto non controllato |
Adaptive Design
Biostatistical Procedures Competing Risk Data Analysis Complex data analysis Data Mining Density Estimation Functional data Gene expression analysis High dimensional statistical methods Image Data Analysis Longitudinal data Mixture Model Analysis Multivariate Survival Data Analysis Network analysis Variable Selection Wavelets fMRI data analysis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00124885 |
| Cham, : Springer, 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Recent advances in robust statistics: theory and applications / Claudio Agostinelli ... [et al.] editors
| Recent advances in robust statistics: theory and applications / Claudio Agostinelli ... [et al.] editors |
| Pubbl/distr/stampa | [New Delhi], : Springer, 2016 |
| Descrizione fisica | X, 201 p. : ill. ; 24 cm |
| Soggetto topico |
00B25 - Proceedings of conferences of miscellaneous specific interest [MSC 2020]
62-XX - Statistics [MSC 2020] 62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020] 62G05 - Nonparametric estimation [MSC 2020] 62G35 - Nonparametric robustness [MSC 2020] 62F35 - Robustness and adaptive procedures (parametric inference) [MSC 2020] |
| Soggetto non controllato |
Data depth
Distance and divergence measures Functional data High-Dimensional Data Robust Statistics Robust dimension reduction Statistical computing |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ita |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0115308 |
| [New Delhi], : Springer, 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Recent advances in robust statistics: theory and applications / Claudio Agostinelli ... [et al.] editors
| Recent advances in robust statistics: theory and applications / Claudio Agostinelli ... [et al.] editors |
| Pubbl/distr/stampa | [New Delhi], : Springer, 2016 |
| Descrizione fisica | X, 201 p. : ill. ; 24 cm |
| Soggetto topico |
00B25 - Proceedings of conferences of miscellaneous specific interest [MSC 2020]
62-XX - Statistics [MSC 2020] 62F35 - Robustness and adaptive procedures (parametric inference) [MSC 2020] 62G05 - Nonparametric estimation [MSC 2020] 62G35 - Nonparametric robustness [MSC 2020] 62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020] |
| Soggetto non controllato |
Data depth
Distance and divergence measures Functional data High-Dimensional Data Robust Statistics Robust dimension reduction Statistical computing |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | This book offers a collection of recent contributions and emerging ideas in the areas of robust statistics presented at the International Conference on Robust Statistics 2015 (ICORS 2015) held in Kolkata during 12–16 January, 2015. The book explores the applicability of robust methods in other non-traditional areas which includes the use of new techniques such as skew and mixture of skew distributions, scaled Bregman divergences, and multilevel functional data methods; application areas being circular data models and prediction of mortality and life expectancy. The contributions are of both theoretical as well as applied in nature. Robust statistics is a relatively young branch of statistical sciences that is rapidly emerging as the bedrock of statistical analysis in the 21st century due to its flexible nature and wide scope. Robust statistics supports the application of parametric and other inference techniques over a broader domain than the strictly interpreted model scenarios employed in classical statistical methods. The aim of the ICORS conference, which is being organized annually since 2001, is to bring together researchers interested in robust statistics, data analysis and related areas. The conference is meant for theoretical and applied statisticians, data analysts from other fields, leading experts, junior researchers and graduate students. The ICORS meetings offer a forum for discussing recent advances and emerging ideas in statistics with a focus on robustness, and encourage informal contacts and discussions among all the participants. They also play an important role in maintaining a cohesive group of international researchers interested in robust statistics and related topics, whose interactions transcend the meetings and endure year round. |
| Record Nr. | UNICAMPANIA-VAN00115308 |
| [New Delhi], : Springer, 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Statistical Learning of Complex Data / Francesca Greselin … [et al.] editors]
| Statistical Learning of Complex Data / Francesca Greselin … [et al.] editors] |
| Pubbl/distr/stampa | Cham, : Springer, 2019 |
| Descrizione fisica | xiii, 201 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62Kxx - Design of statistical experiments [MSC 2020] 62Gxx - Nonparametric inference [MSC 2020] 62Hxx - Multivariate analysis [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] 62Jxx - Linear inference, regression [MSC 2020] 62Fxx - Parametric inference [MSC 2020] 68T09 - Computational aspects of data analysis and big data [MSC 2020] |
| Soggetto non controllato |
Big Data
Classification Clustering Complex data Data analysis Explanatory data analysis Functional data Graphical Models Machine learning methods Multidimensional Scaling Multiway data Network data Pattern recognition Statistical learning Statistical modeling |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0127162 |
| Cham, : Springer, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Statistical Learning of Complex Data / Francesca Greselin … [et al.] editors]
| Statistical Learning of Complex Data / Francesca Greselin … [et al.] editors] |
| Pubbl/distr/stampa | Cham, : Springer, 2019 |
| Descrizione fisica | xiii, 201 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62Fxx - Parametric inference [MSC 2020] 62Gxx - Nonparametric inference [MSC 2020] 62Hxx - Multivariate analysis [MSC 2020] 62Jxx - Linear inference, regression [MSC 2020] 62Kxx - Design of statistical experiments [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] 68T09 - Computational aspects of data analysis and big data [MSC 2020] |
| Soggetto non controllato |
Big Data
Classification Clustering Complex data Data Analysis Explanatory data analysis Functional data Graphical models Machine learning methods Multidimensional Scaling Multiway data Network data Pattern recognition Statistical learning Statistical modeling |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00127162 |
| Cham, : Springer, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
