robust rank based nonparametric methods (22 résultats)

Etat : New. In.

Etat : New. In.

Etat : New. pp. XIV, 277 31 illus., 6 illus. in color. 1 Edition NO-PA16APR2015-KAP.

Taschenbuch. Etat : Neu. Robust Rank-Based and Nonparametric Methods | Michigan, USA, April 2015: Selected, Revised, and Extended Contributions | Regina Y. Liu (u. a.) | Taschenbuch | Springer Proceedings in Mathematics & Statistics | xiv | Englisch | 2018 | Springer | EAN 9783319818092 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaboratedwith Joseph McKean to develop underlying theory for these methods,obtain small sample corrections, and develop efficient algorithmsfor their computation.The papers cover the scope of the area, includingrobust nonparametric rank-based procedures through Bayesian and big datarank-based analyses.Areas of application include biostatistics andspatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably.These procedures generalize traditional Wilcoxon-type methods for one- andtwo-sample location problems.Research into these procedures has culminated in complete analyses for manyof the models used in practice including linear, generalized linear, mixed,and nonlinear models. Settings are both multivariate and univariate.With the development of R packages in these areas, computation of these procedures is easilyshared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaboratedwith Joseph McKean to develop underlying theory for these methods,obtain small sample corrections, and develop efficient algorithmsfor their computation.The papers cover the scope of the area, includingrobust nonparametric rank-based procedures through Bayesian and big datarank-based analyses.Areas of application include biostatistics andspatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably.These procedures generalize traditional Wilcoxon-type methods for one- andtwo-sample location problems.Research into these procedures has culminated in complete analyses for manyof the models used in practice including linear, generalized linear, mixed,and nonlinear models. Settings are both multivariate and univariate.With the development of R packages in these areas, computation of these procedures is easilyshared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015.

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Etat : new. Questo è un articolo print on demand.

Etat : new. Questo è un articolo print on demand.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware - The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaboratedwith Joseph McKean to develop underlying theory for these methods,obtain small sample corrections, and develop efficient algorithmsfor their computation.The papers cover the scope of the area, includingrobust nonparametric rank-based procedures through Bayesian and big datarank-based analyses.Areas of application include biostatistics andspatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably.These procedures generalize traditional Wilcoxon-type methods for one- andtwo-sample location problems.Research into these procedures has culminated in complete analyses for manyof the models used in practice including linear, generalized linear, mixed,and nonlinear models. Settings are both multivariate and univariate.With the development of R packages in these areas, computation of these procedures is easilyshared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015. 292 pp. Englisch.

Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware - The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaboratedwith Joseph McKean to develop underlying theory for these methods,obtain small sample corrections, and develop efficient algorithmsfor their computation.The papers cover the scope of the area, includingrobust nonparametric rank-based procedures through Bayesian and big datarank-based analyses.Areas of application include biostatistics andspatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably.These procedures generalize traditional Wilcoxon-type methods for one- andtwo-sample location problems.Research into these procedures has culminated in complete analyses for manyof the models used in practice including linear, generalized linear, mixed,and nonlinear models. Settings are both multivariate and univariate.With the development of R packages in these areas, computation of these procedures is easilyshared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015. 292 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Regina Liu is currently Distinguished Professor of Statistics at Rutgers University, USA. She received her Ph.D. from Columbia University at New York. She has published extensively in a broad range of research areas, including nonparametric .

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Regina Liu is currently Distinguished Professor of Statistics at Rutgers University, USA. She received her Ph.D. from Columbia University at New York. She has published extensively in a broad range of research areas, including nonparametric .

Etat : New. Print on Demand pp. XIV, 277 31 illus., 6 illus. in color.

Etat : New. PRINT ON DEMAND pp. XIV, 277 31 illus., 6 illus. in color.

Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 292 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 292 pp. Englisch.

Etat : New. Print on Demand pp. 330.

Etat : New. PRINT ON DEMAND pp. 330.