Modern Applied Statistics with S-PLUS

Modern Applied Statistics with S-PLUS

Author: William N. Venables

Publisher: Springer Science & Business Media

Published: 2013-11-11

Total Pages: 562

ISBN-13: 1475727194

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A guide to using the power of S-PLUS to perform statistical analyses, providing both an introduction to the program and a course in modern statistical methods. Readers are assumed to have a basic grounding in statistics, thus the book is intended for would-be users, as well as students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets, with many of the methods discussed being modern approaches to topics such as linear and non-linear regression models, robust and smooth regression methods, survival analysis, multivariate analysis, tree-based methods, time series, spatial statistics, and classification. This second edition is intended for users of S-PLUS 3.3, or later, and covers both Windows and UNIX. It treats the recent developments in graphics and new statistical functionality, including bootstraping, mixed effects linear and non-linear models, factor analysis, and regression with autocorrelated errors. The authors have written several software libraries which enhance S-PLUS, and these, plus all the datasets used, are available on the Internet.


Modern Applied U-Statistics

Modern Applied U-Statistics

Author: Jeanne Kowalski

Publisher: John Wiley & Sons

Published: 2008-01-28

Total Pages: 402

ISBN-13: 0470186453

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A timely and applied approach to the newly discovered methods and applications of U-statistics Built on years of collaborative research and academic experience, Modern Applied U-Statistics successfully presents a thorough introduction to the theory of U-statistics using in-depth examples and applications that address contemporary areas of study including biomedical and psychosocial research. Utilizing a "learn by example" approach, this book provides an accessible, yet in-depth, treatment of U-statistics, as well as addresses key concepts in asymptotic theory by integrating translational and cross-disciplinary research. The authors begin with an introduction of the essential and theoretical foundations of U-statistics such as the notion of convergence in probability and distribution, basic convergence results, stochastic Os, inference theory, generalized estimating equations, as well as the definition and asymptotic properties of U-statistics. With an emphasis on nonparametric applications when and where applicable, the authors then build upon this established foundation in order to equip readers with the knowledge needed to understand the modern-day extensions of U-statistics that are explored in subsequent chapters. Additional topical coverage includes: Longitudinal data modeling with missing data Parametric and distribution-free mixed-effect and structural equation models A new multi-response based regression framework for non-parametric statistics such as the product moment correlation, Kendall's tau, and Mann-Whitney-Wilcoxon rank tests A new class of U-statistic-based estimating equations (UBEE) for dependent responses Motivating examples, in-depth illustrations of statistical and model-building concepts, and an extensive discussion of longitudinal study designs strengthen the real-world utility and comprehension of this book. An accompanying Web site features SAS? and S-Plus? program codes, software applications, and additional study data. Modern Applied U-Statistics accommodates second- and third-year students of biostatistics at the graduate level and also serves as an excellent self-study for practitioners in the fields of bioinformatics and psychosocial research.


S Programming

S Programming

Author: William Venables

Publisher: Springer Science & Business Media

Published: 2000-04-20

Total Pages: 284

ISBN-13: 9780387989662

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Written by the bestselling authors of "Modern Applied Statistics with S-Plus", this book provides an in-depth guide to writing software in the S language under the commercial S-PLUS and the Open Source R systems. The book is geared to those with some knowledge of the S language who want to use it more effectively.


Modern Applied Statistics with S

Modern Applied Statistics with S

Author: W.N. Venables

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 501

ISBN-13: 0387217061

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A guide to using S environments to perform statistical analyses providing both an introduction to the use of S and a course in modern statistical methods. The emphasis is on presenting practical problems and full analyses of real data sets.


Applying Contemporary Statistical Techniques

Applying Contemporary Statistical Techniques

Author: Rand R. Wilcox

Publisher: Gulf Professional Publishing

Published: 2003-01-06

Total Pages: 688

ISBN-13: 9780127515410

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Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible. Highlights: * Assumes no previous training in statistics * Explains when and why modern methods provide more accurate results * Provides simple descriptions of when and why conventional methods can be highly unsatisfactory * Covers the latest developments on multiple comparisons * Includes recent advances in risk-based methods * Features many illustrations and examples using data from real studies * Describes and illustrates easy-to-use s-plus functions for applying cutting-edge techniques "The book is quite unique in that it offers a lot of up-to-date statistical tools. No other book at this level comes close in this aspect." Xuming He -University of Illinois, Urbana


Modern Applied Statistics with S-Plus

Modern Applied Statistics with S-Plus

Author: W.N. Venables

Publisher: Springer

Published: 2013-11-11

Total Pages: 467

ISBN-13: 1489928197

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A guide to using S-Plus to perform statistical analyses, serving as both an introduction to the use of S-Plus and as a course in modern statistical methods. The experienced authors show how to use S-Plus as a powerful and graphical system, with the emphasis on presenting practical problems and full analyses of real data sets throughout. A basic grounding in statistics is assumed, making this book suitable for would-be users of S-Plus, as well as students and researchers using statistics.


Statistical Analysis of Financial Data in S-Plus

Statistical Analysis of Financial Data in S-Plus

Author: René Carmona

Publisher: Springer Science & Business Media

Published: 2006-04-18

Total Pages: 456

ISBN-13: 0387218246

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This is the first book at the graduate textbook level to discuss analyzing financial data with S-PLUS. Its originality lies in the introduction of tools for the estimation and simulation of heavy tail distributions and copulas, the computation of measures of risk, and the principal component analysis of yield curves. The book is aimed at undergraduate students in financial engineering; master students in finance and MBA's, and to practitioners with financial data analysis concerns.


Applied Statistics with SPSS

Applied Statistics with SPSS

Author: Eelko Huizingh

Publisher: SAGE

Published: 2007-01-24

Total Pages: 368

ISBN-13: 1446223000

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Accessibly written and easy to use, Applied Statistics Using SPSS is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. Based around the needs of undergraduate students embarking on their own research project, the text′s self-help style is designed to boost the skills and confidence of those that will need to use SPSS in the course of doing their research project. The book is pedagogically well developed and contains many screen dumps and exercises, glossary terms and worked examples. Divided into two parts, Applied Statistics Using SPSS covers : 1. A self-study guide for learning how to use SPSS. 2. A reference guide for selecting the appropriate statistical technique and a stepwise do-it-yourself guide for analysing data and interpreting the results. 3. Readers of the book can download the SPSS data file that is used for most of the examples throughout the book. Geared explicitly for undergraduate needs, this is an easy to follow SPSS book that should provide a step-by-step guide to research design and data analysis using SPSS.


Modern Data Science with R

Modern Data Science with R

Author: Benjamin S. Baumer

Publisher: CRC Press

Published: 2021-03-31

Total Pages: 830

ISBN-13: 0429575394

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From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.


The R Book

The R Book

Author: Michael J. Crawley

Publisher: John Wiley & Sons

Published: 2007-06-13

Total Pages: 953

ISBN-13: 9780470515068

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The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.