Modern Applied Statistics with S (Record no. 27367)

000 -LEADER
fixed length control field 07486nam a22006255i 4500
001 - CONTROL NUMBER
control field 978-0-387-21706-2
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240716150904.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
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007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 121227s2002 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780387217062
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-0-387-21706-2
Source of number or code doi
040 ## - CATALOGING SOURCE
Transcribing agency imu-kc
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA273.A1-274.9
072 #7 - SUBJECT CATEGORY CODE
Subject category code PBT
Source bicssc
Subject category code PBWL
Source bicssc
Subject category code MAT029000
Source bisacsh
Subject category code PBT
Source thema
Subject category code PBWL
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.2
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Venables, W.N.
Relator term author.
Relationship aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Modern Applied Statistics with S
Medium [electronic resource] /
Statement of responsibility, etc. by W.N. Venables, B.D. Ripley.
250 ## - EDITION STATEMENT
Edition statement 4th ed. 2002.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture New York, NY :
Name of producer, publisher, distributor, manufacturer Springer New York :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2002.
300 ## - PHYSICAL DESCRIPTION
Extent XII, 498 p.
Other physical details online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
490 1# - SERIES STATEMENT
Series statement Statistics and Computing,
International Standard Serial Number 2197-1706
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1 Introduction -- 1.1 A Quick Overview of S -- 1.2 Using S -- 1.3 An Introductory Session -- 1.4 What Next? -- 2 Data Manipulation -- 2.1 Objects -- 2.2 Connections -- 2.3 Data Manipulation -- 2.4 Tables and Cross-Classification -- 3 The S Language -- 3.1 Language Layout -- 3.2 More on S Objects -- 3.3 Arithmetical Expressions -- 3.4 Character Vector Operations -- 3.5 Formatting and Printing -- 3.6 Calling Conventions for Functions -- 3.7 Model Formulae -- 3.8 Control Structures -- 3.9 Array and Matrix Operations -- 3.10 Introduction to Classes and Methods -- 4 Graphics -- 4.1 Graphics Devices -- 4.2 Basic Plotting Functions -- 4.3 Enhancing Plots -- 4.4 Fine Control of Graphics -- 4.5 Trellis Graphics -- 5 Univariate Statistics -- 5.1 Probability Distributions -- 5.2 Generating Random Data -- 5.3 Data Summaries -- 5.4 Classical Univariate Statistics -- 5.5 Robust Summaries -- 5.6 Density Estimation -- 5.7 Bootstrap and Permutation Methods -- 6 Linear Statistical Models -- 6.1 An Analysis of Covariance Example -- 6.2 Model Formulae and Model Matrices -- 6.3 Regression Diagnostics -- 6.4 Safe Prediction -- 6.5 Robust and Resistant Regression -- 6.6 Bootstrapping Linear Models -- 6.7 Factorial Designs and Designed Experiments -- 6.8 An Unbalanced Four-Way Layout -- 6.9 Predicting Computer Performance -- 6.10 Multiple Comparisons -- 7 Generalized Linear Models -- 7.1 Functions for Generalized Linear Modelling -- 7.2 Binomial Data -- 7.3 Poisson and Multinomial Models -- 7.4 A Negative Binomial Family -- 7.5 Over-Dispersion in Binomial and Poisson GLMs -- 8 Non-Linear and Smooth Regression -- 8.1 An Introductory Example -- 8.2 Fitting Non-Linear Regression Models -- 8.3 Non-Linear Fitted Model Objects and Method Functions -- 8.4 Confidence Intervals for Parameters -- 8.5 Profiles -- 8.6 Constrained Non-Linear Regression -- 8.7 One-Dimensional Curve-Fitting -- 8.8 Additive Models -- 8.9 Projection-Pursuit Regression -- 8.10 Neural Networks -- 8.11 Conclusions -- 9 Tree-Based Methods -- 9.1 Partitioning Methods -- 9.2 Implementation in rpart -- 9.3 Implementation in tree -- 10 Random and Mixed Effects -- 10.1 Linear Models -- 10.2 Classic Nested Designs -- 10.3 Non-Linear Mixed Effects Models -- 10.4 Generalized Linear Mixed Models -- 10.5 GEE Models -- 11 Exploratory Multivariate Analysis -- 11.1 Visualization Methods -- 11.2 Cluster Analysis -- 11.3 Factor Analysis -- 11.4 Discrete Multivariate Analysis -- 12 Classification -- 12.1 Discriminant Analysis -- 12.2 Classification Theory -- 12.3 Non-Parametric Rules -- 12.4 Neural Networks -- 12.5 Support Vector Machines -- 12.6 Forensic Glass Example -- 12.7 Calibration Plots -- 13 Survival Analysis -- 13.1 Estimators of Survivor Curves -- 13.2 Parametric Models -- 13.3 Cox Proportional Hazards Model -- 13.4 Further Examples -- 14 Time Series Analysis -- 14.1 Second-Order Summaries -- 14.2 ARIMA Models -- 14.3 Seasonality -- 14.4 Nottingham Temperature Data -- 14.5 Regression with Autocorrelated Errors -- 14.6 Models for Financial Series -- 15 Spatial Statistics -- 15.1 Spatial Interpolation and Smoothing -- 15.2 Kriging -- 15.3 Point Process Analysis -- 16 Optimization -- 16.1 Univariate Functions -- 16.2 Special-Purpose Optimization Functions -- 16.3 General Optimization -- Appendices -- A Implementation-Specific Details -- A.1 Using S-PLUS under Unix / Linux -- A.2 Using S-PLUS under Windows -- A.3 Using R under Unix / Linux -- A.4 Using R under Windows -- A.5 For Emacs Users -- B The S-PLUS GUI -- C Datasets, Software and Libraries -- C.1 Our Software -- C.2 Using Libraries -- References.
520 ## - SUMMARY, ETC.
Summary, etc. S is a powerful environment for the statistical and graphical analysis of data. It provides the tools to implement many statistical ideas that have been made possible by the widespread availability of workstations having good graphics and computational capabilities. This book is a guide to using S environments to perform statistical analyses and provides both an introduction to the use of S and a course in modern statistical methods. Implementations of S are available commercially in S-PLUS(R) workstations and as the Open Source R for a wide range of computer systems. The aim of this book is to show how to use S as a powerful and graphical data analysis system. Readers are assumed to have a basic grounding in statistics, and so the book is intended for would-be users of S-PLUS or R and both students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets. Many of the methods discussed are state of the art approaches to topics such as linear, nonlinear and smooth regression models, tree-based methods, multivariate analysis, pattern recognition, survival analysis, time series and spatial statistics. Throughout modern techniques such as robust methods, non-parametric smoothing and bootstrapping are used where appropriate. This fourth edition is intended for users of S-PLUS 6.0 or R 1.5.0 or later. A substantial change from the third edition is updating for the current versions of S-PLUS and adding coverage of R. The introductory material has been rewritten to emphasis the import, export and manipulation of data. Increased computational power allows even more computer-intensive methods to be used, and methods such as GLMMs,.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Probabilities.
Topical term or geographic name entry element Mathematics
General subdivision Data processing.
Topical term or geographic name entry element Computer software.
Topical term or geographic name entry element Mathematical statistics
General subdivision Data processing.
Topical term or geographic name entry element Statistics .
Topical term or geographic name entry element Probability Theory.
Topical term or geographic name entry element Computational Mathematics and Numerical Analysis.
Topical term or geographic name entry element Mathematical Software.
Topical term or geographic name entry element Statistics and Computing.
Topical term or geographic name entry element Statistical Theory and Methods.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Ripley, B.D.
Relator term author.
Relationship aut
-- http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9780387892009
Relationship information Printed edition:
International Standard Book Number 9781441930088
Relationship information Printed edition:
International Standard Book Number 9780387954578
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Statistics and Computing,
International Standard Serial Number 2197-1706
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-0-387-21706-2">https://doi.org/10.1007/978-0-387-21706-2</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type E-Book

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