Nonparametric... - Focusing on robust rank-based nonparametric methods, this book covers rank-based fitting and testing for models ranging from simple location models to general linear mo… Mehr…
Nonparametric... - Focusing on robust rank-based nonparametric methods, this book covers rank-based fitting and testing for models ranging from simple location models to general linear models for uncorrelated and correlated responses. Illustrated with real data examples using R, each chapter includes a short problem set with data sets. The corresponding example codes are available online. Accessible to nonspecialists, the book also offers an appendix with the technical details of the geometry of rank-based estimation. John Kloke is a biostatistician and assistant scientist at the University of Wisconsin-Madison. He has held faculty positions at the University of Pittsburgh, Bucknell University, and Pomona College. An R user for more than 15 years, he is an author and maintainer of numerous R packages, including Rfit and npsm. He has published papers on nonparametric rank-based estimation, including analysis of cluster correlated data. Joseph W. McKean is a professor of statistics at Western Michigan University. He has published many papers on nonparametric and robust statistical procedures and has co-authored several books, including Robust Nonparametric Statistical Methods and Introduction to Mathematical Statistics. He is an associate editor of several statistics journals and a fellow of the American Statistical Association. Getting Started with R R Basics Reading External Data Generating Random Data Graphics Repeating Tasks User-Defined Functions Monte Carlo Simulation R Packages Basic Statistics Sign Test Signed-Rank Wilcoxon Bootstrap Robustness One- and Two-Sample Proportion Problems chi2 Tests Two-Sample Problems Introductory Example Rank-Based Analyses Scale Problem Placement Test for the Behrens-Fisher Problem Efficiency and Optimal Scores Adaptive Rank Scores Tests Regression I Simple Linear Regression Multiple Linear Regression Linear Models Aligned Rank Tests Bootstrap Nonparametric Regression Correlation ANOVA and ANCOVA One-Way ANOVA Multi-Way Crossed Factorial Design ANCOVA Methodology for Type III Hypotheses Testing Ordered Alternatives Multi-Sample Scale Problem Time-to-Event Analysis Kaplan-Meier and Log Rank Test Cox Proportional Hazards Models Accelerated Failure Time Models Regression II Robust Diagnostics Weighted Regression Linear Models with Skew Normal Errors A Hogg-Type Adaptive Procedure Nonlinear Time Series Cluster Correlated Data Friedman's Test Joint Rankings Estimator Robust Variance Component Estimators Multiple Rankings Estimator GEE-Type Estimator Bibliography Index Exercises appear at the end of each chapter. Livre - Beau livre, [PU: Productivity Press]<
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A Practical Guide to Implementing Nonparametric and Rank-Based ProceduresNonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, includ… Mehr…
A Practical Guide to Implementing Nonparametric and Rank-Based ProceduresNonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm.The book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data.The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R. New Textbooks>Hardcover>Science>Statistics & Probability>Statistics & Probability, Taylor & Francis Core >2 >T<
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A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, in… Mehr…
A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm. The book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data. The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R. Books, [PU: Productivity Press]<
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[EAN: 9781439873434], Neubuch, [PU: Chapman and Hall/CRC], MATHEMATICS PROBABILITY & STATISTICS GENERAL, Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer… Mehr…
[EAN: 9781439873434], Neubuch, [PU: Chapman and Hall/CRC], MATHEMATICS PROBABILITY & STATISTICS GENERAL, Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Über den AutorJohn Kloke is a biostatistician and assistant scientist at the University of Wisconsin-Madison. He has held faculty positions at the University of Pittsburgh, Bucknell University, and Pomona College. An R user for more., Books<
1st Edition, by John Kloke; Joseph W. McKean, PRINT ISBN: 9781439873434 E-TEXT ISBN: 9781439873441 Additional ISBNs: 1439873437, 0429104855, 0367739720, 9781439873434, 9780429104855, 9780… Mehr…
1st Edition, by John Kloke; Joseph W. McKean, PRINT ISBN: 9781439873434 E-TEXT ISBN: 9781439873441 Additional ISBNs: 1439873437, 0429104855, 0367739720, 9781439873434, 9780429104855, 9780367739720, 1439873445, 1322624380, 9781439873441, 9781322624389 Taylor & Francis eBook Other pricing structure might be available at vitalsource.com., Chapman & Hall<
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Nonparametric... - Focusing on robust rank-based nonparametric methods, this book covers rank-based fitting and testing for models ranging from simple location models to general linear mo… Mehr…
Nonparametric... - Focusing on robust rank-based nonparametric methods, this book covers rank-based fitting and testing for models ranging from simple location models to general linear models for uncorrelated and correlated responses. Illustrated with real data examples using R, each chapter includes a short problem set with data sets. The corresponding example codes are available online. Accessible to nonspecialists, the book also offers an appendix with the technical details of the geometry of rank-based estimation. John Kloke is a biostatistician and assistant scientist at the University of Wisconsin-Madison. He has held faculty positions at the University of Pittsburgh, Bucknell University, and Pomona College. An R user for more than 15 years, he is an author and maintainer of numerous R packages, including Rfit and npsm. He has published papers on nonparametric rank-based estimation, including analysis of cluster correlated data. Joseph W. McKean is a professor of statistics at Western Michigan University. He has published many papers on nonparametric and robust statistical procedures and has co-authored several books, including Robust Nonparametric Statistical Methods and Introduction to Mathematical Statistics. He is an associate editor of several statistics journals and a fellow of the American Statistical Association. Getting Started with R R Basics Reading External Data Generating Random Data Graphics Repeating Tasks User-Defined Functions Monte Carlo Simulation R Packages Basic Statistics Sign Test Signed-Rank Wilcoxon Bootstrap Robustness One- and Two-Sample Proportion Problems chi2 Tests Two-Sample Problems Introductory Example Rank-Based Analyses Scale Problem Placement Test for the Behrens-Fisher Problem Efficiency and Optimal Scores Adaptive Rank Scores Tests Regression I Simple Linear Regression Multiple Linear Regression Linear Models Aligned Rank Tests Bootstrap Nonparametric Regression Correlation ANOVA and ANCOVA One-Way ANOVA Multi-Way Crossed Factorial Design ANCOVA Methodology for Type III Hypotheses Testing Ordered Alternatives Multi-Sample Scale Problem Time-to-Event Analysis Kaplan-Meier and Log Rank Test Cox Proportional Hazards Models Accelerated Failure Time Models Regression II Robust Diagnostics Weighted Regression Linear Models with Skew Normal Errors A Hogg-Type Adaptive Procedure Nonlinear Time Series Cluster Correlated Data Friedman's Test Joint Rankings Estimator Robust Variance Component Estimators Multiple Rankings Estimator GEE-Type Estimator Bibliography Index Exercises appear at the end of each chapter. Livre - Beau livre, [PU: Productivity Press]<
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A Practical Guide to Implementing Nonparametric and Rank-Based ProceduresNonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, includ… Mehr…
A Practical Guide to Implementing Nonparametric and Rank-Based ProceduresNonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm.The book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data.The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R. New Textbooks>Hardcover>Science>Statistics & Probability>Statistics & Probability, Taylor & Francis Core >2 >T<
A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, in… Mehr…
A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm. The book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data. The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R. Books, [PU: Productivity Press]<
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[EAN: 9781439873434], Neubuch, [PU: Chapman and Hall/CRC], MATHEMATICS PROBABILITY & STATISTICS GENERAL, Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer… Mehr…
[EAN: 9781439873434], Neubuch, [PU: Chapman and Hall/CRC], MATHEMATICS PROBABILITY & STATISTICS GENERAL, Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Über den AutorJohn Kloke is a biostatistician and assistant scientist at the University of Wisconsin-Madison. He has held faculty positions at the University of Pittsburgh, Bucknell University, and Pomona College. An R user for more., Books<
1st Edition, by John Kloke; Joseph W. McKean, PRINT ISBN: 9781439873434 E-TEXT ISBN: 9781439873441 Additional ISBNs: 1439873437, 0429104855, 0367739720, 9781439873434, 9780429104855, 9780… Mehr…
1st Edition, by John Kloke; Joseph W. McKean, PRINT ISBN: 9781439873434 E-TEXT ISBN: 9781439873441 Additional ISBNs: 1439873437, 0429104855, 0367739720, 9781439873434, 9780429104855, 9780367739720, 1439873445, 1322624380, 9781439873441, 9781322624389 Taylor & Francis eBook Other pricing structure might be available at vitalsource.com., Chapman & Hall<
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A Practical Guide to Implementing Nonparametric and Rank-Based Procedures
Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm.
The book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data.
The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R.
Detailangaben zum Buch - Nonparametric Statistical Methods Using R John Kloke Author
EAN (ISBN-13): 9781439873434 ISBN (ISBN-10): 1439873437 Gebundene Ausgabe Taschenbuch Erscheinungsjahr: 2014 Herausgeber: Taylor & Francis Core >2 >T
Buch in der Datenbank seit 2011-06-06T20:57:47+02:00 (Berlin) Detailseite zuletzt geändert am 2022-09-28T17:22:02+02:00 (Berlin) ISBN/EAN: 9781439873434
ISBN - alternative Schreibweisen: 1-4398-7343-7, 978-1-4398-7343-4 Alternative Schreibweisen und verwandte Suchbegriffe: Autor des Buches: kloke, john mckean, klok, taylor Titel des Buches: statistical methods, nonparametric statistical, chapman
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