Search Results: environmentalstats-for-s-plusÃ-Â-user-s-manual-for-version-2-0

EnvironmentalStats for S-Plus®

User’s Manual for Version 2.0

Author: Steven P. Millard

Publisher: Springer Science & Business Media

ISBN: 1461300436

Category: Science

Page: 264

View: 9596

This is the User's Manual to the software package EnvironmentalStats for S-PLUS, which is an add-on module for S-PLUS providing the first comprehensive software package for environmental scientists, engineers, and regulators. The new edition provides the documentation for Version 2.0 (which runs under S-PLUS 6.0), and includes extensive examples using real data sets.

Programming with Data

A Guide to the S Language

Author: John M. Chambers

Publisher: Springer Science & Business Media

ISBN: 9780387985039

Category: Computers

Page: 469

View: 2235

Here is a thorough and authoritative guide to the latest version of the S language and to its programming environment the premier software platform for computing with data. Programming with Data describes a new and greatly extended version of S and is written by the chief designer of the language. The book is a guide to the complete programming process, starting from simple interactive use and continuing through ambitious software projects. S is designed for computing with data-for any project in which organizing, visualizing, summarizing, or modeling data are central concerns. Its focus is on the needs of the programmer/user, and its goal is "to turn ideas into software, quickly and faithfully." S is a functional object-based language with a huge library of functions for all aspects of computing with data. Its long and enthusiastic use in statistics and applied fields has also led to many valuable libraries of user-written functions. The new version of S provides powerful class/method structure, new techniques to deal with large objects, extended interfaces to other languages and files, object-based documentation compatible with HTML, and powerful new interactive programming techniques. This version of S underlies the S-PLUS system, versions 5*0 and higher.

American Book Publishing Record

Author: N.A

Publisher: N.A

ISBN: N.A

Category: Books

Page: N.A

View: 1319

EnvStats

An R Package for Environmental Statistics

Author: Steven P. Millard

Publisher: Springer Science & Business Media

ISBN: 1461484561

Category: Computers

Page: 291

View: 8298

This book describes EnvStats, a new comprehensive R package for environmental statistics and the successor to the S-PLUS module EnvironmentalStats for S-PLUS (first released in 1997). EnvStats and R provide an open-source set of powerful functions for performing graphical and statistical analyses of environmental data, bringing major environmental statistical methods found in the literature and regulatory guidance documents into one statistical package, along with an extensive hypertext help system that explains what these methods do, how to use these methods, and where to find them in the environmental statistics literature. EnvStats also includes numerous built-in data sets from regulatory guidance documents and the environmental statistics literature. This book shows how to use EnvStats and R to easily: * graphically display environmental data * plot probability distributions * estimate distribution parameters and construct confidence intervals on the original scale for commonly used distributions such as the lognormal and gamma, as well as do this nonparametrically * estimate and construct confidence intervals for distribution percentiles or do this nonparametrically (e.g., to compare to an environmental protection standard) * perform and plot the results of goodness-of-fit tests * compute optimal Box-Cox data transformations * compute prediction limits and simultaneous prediction limits (e.g., to assess compliance at multiple sites for multiple constituents) * perform nonparametric estimation and test for seasonal trend (even in the presence of correlated observations) * perform power and sample size computations and create companion plots for sampling designs based on confidence intervals, hypothesis tests, prediction intervals, and tolerance intervals * deal with non-detect (censored) data * perform Monte Carlo simulation and probabilistic risk assessment * reproduce specific examples in EPA guidance documents EnvStats combined with other R packages (e.g., for spatial analysis) provides the environmental scientist, statistician, researcher, and technician with tools to “get the job done!”

Books in Print

Author: N.A

Publisher: N.A

ISBN: N.A

Category: American literature

Page: N.A

View: 4072

Books in print is the major source of information on books currently published and in print in the United States. The database provides the record of forthcoming books, books in-print, and books out-of-print.

American Book Publishing Record

BPR cumulative

Author: Bowker Staff

Publisher: R. R. Bowker

ISBN: 9780835240857

Category: Reference

Page: 17426

View: 4544

Cumulative Book Index

Author: N.A

Publisher: N.A

ISBN: N.A

Category: American literature

Page: N.A

View: 4548

Environmental Statistics with S-PLUS

Author: Steven P. Millard,Nagaraj K. Neerchal

Publisher: CRC Press

ISBN: 142003717X

Category: Mathematics

Page: 848

View: 7873

A clear, comprehensive treatment of the subject, Environmental Statistics with S-PLUS surveys the vast array of statistical methods used to collect and analyze environmental data. The book explains what these methods are, how to use them, and where to find references to them. In addition, it provides insight into what to think about before you collect environmental data, how to collect the data, and how to make sense of it after collection. A unique and powerful feature of the book is its integration with the commercially available software package S-Plus and the add-on modules EnvironmentalStats for S-PLUS, S+SpatialStats, and S-PLUS for ArcView. The book presents data sets to explain statistical methods, and then shows how to implement these methods by providing the commands for and the results from the software. This survey of statistical methods, definitions, and concepts helps you collect and effectively analyze data for environmental pollution problems. Using the S-PLUS software in conjunction with this text will no doubt increase understanding of the methods.

Nondetects and Data Analysis

Statistics for Censored Environmental Data

Author: Dennis R. Helsel,USGS

Publisher: Wiley-Interscience

ISBN: N.A

Category: Mathematics

Page: 250

View: 2940

STATISTICS IN PRACTICE Statistical methods for interpreting and analyzing censored environmental data Nondetects And Data Analysis: Statistics for Censored Environmental Data provides solutions for environmental scientists and professionals who need to interpret and analyze data that fall below the laboratory detection limit. Adapting survival analysis methods that have been successfully used in medical and industrial research, the author demonstrates, for the first time, their practical applications for studies of trace chemicals in air, water, soils, and biota. Readers quickly become proficient in these methods through the use of real-world examples that are solved using MINITAB® Release 14, a popular statistical software package, as well as other commonly used software packages. Everything needed to master these innovative statistical methods is provided, including: Accompanying Web site featuring answers to book exercises and datasets, as well as MINITAB® macros to perform methods, which are not available in the commercial version Methods for data with multiple detection limits Solutions for research studies in which all data are below detection limits Techniques for constructing confidence, prediction, and tolerance intervals for data with nond-tects Methods for data with multiple detection limits Chapters are organized by objective, such as computing intervals, comparing groups, and correlations, which enables readers to more easily apply the text to their particular research and goals. Extensive references to the literature for more in-depth research are provided; however, the text itself avoids complex math and calculus making it accessible to anyone in the environmental sciences. Environmental scientists and professionals will find the hands-on guidance and practical examples invaluable.

Acid Rain - Deposition to Recovery

Author: Peter Brimblecombe,Hiroshi Hara,Daniel Houle,Martin Novak

Publisher: Springer Science & Business Media

ISBN: 9781402058851

Category: Science

Page: 419

View: 4728

This book looks at the sources and composition of the atmosphere and rainfall, with particular attention on acidifying components and those that affect ecosystems. It further widens the subject to look at trace metals. It includes papers on the impact of deposition on soils and forests and the recovery of the natural environment. Work on critical loads makes a contribution to understanding the degree to which deposition must be reduced to limit its impact.

Regression

Linear Models in Statistics

Author: N. H. Bingham,John M. Fry

Publisher: Springer Science & Business Media

ISBN: 9781848829695

Category: Mathematics

Page: 284

View: 5817

Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error. The subject is inherently two- or higher- dimensional, thus an understanding of Statistics in one dimension is essential. Regression: Linear Models in Statistics fills the gap between introductory statistical theory and more specialist sources of information. In doing so, it provides the reader with a number of worked examples, and exercises with full solutions. The book begins with simple linear regression (one predictor variable), and analysis of variance (ANOVA), and then further explores the area through inclusion of topics such as multiple linear regression (several predictor variables) and analysis of covariance (ANCOVA). The book concludes with special topics such as non-parametric regression and mixed models, time series, spatial processes and design of experiments. Aimed at 2nd and 3rd year undergraduates studying Statistics, Regression: Linear Models in Statistics requires a basic knowledge of (one-dimensional) Statistics, as well as Probability and standard Linear Algebra. Possible companions include John Haigh’s Probability Models, and T. S. Blyth & E.F. Robertsons’ Basic Linear Algebra and Further Linear Algebra.

Indigenous Data Sovereignty

Toward an agenda

Author: Tahu Kukutai,John Taylor

Publisher: ANU Press

ISBN: 1760460311

Category: Social Science

Page: 318

View: 5695

As the global ‘data revolution’ accelerates, how can the data rights and interests of indigenous peoples be secured? Premised on the United Nations Declaration on the Rights of Indigenous Peoples, this book argues that indigenous peoples have inherent and inalienable rights relating to the collection, ownership and application of data about them, and about their lifeways and territories. As the first book to focus on indigenous data sovereignty, it asks: what does data sovereignty mean for indigenous peoples, and how is it being used in their pursuit of self-determination? The varied group of mostly indigenous contributors theorise and conceptualise this fast-emerging field and present case studies that illustrate the challenges and opportunities involved. These range from indigenous communities grappling with issues of identity, governance and development, to national governments and NGOs seeking to formulate a response to indigenous demands for data ownership. While the book is focused on the CANZUS states of Canada, Australia, Aotearoa/New Zealand and the United States, much of the content and discussion will be of interest and practical value to a broader global audience. ‘A debate-shaping book … it speaks to a fast-emerging field; it has a lot of important things to say; and the timing is right.’ — Stephen Cornell, Professor of Sociology and Faculty Chair of the Native Nations Institute, University of Arizona ‘The effort … in this book to theorise and conceptualise data sovereignty and its links to the realisation of the rights of indigenous peoples is pioneering and laudable.’ — Victoria Tauli-Corpuz, UN Special Rapporteur on the Rights of Indigenous Peoples, Baguio City, Philippines

Statistical Data Analysis Explained

Applied Environmental Statistics with R

Author: Clemens Reimann,Peter Filzmoser,Robert Garrett,Rudolf Dutter

Publisher: John Wiley & Sons

ISBN: 1119965284

Category: Science

Page: 362

View: 7160

Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This is a book written in colloquial language, avoiding mathematical formulae as much as possible, trying to explain statistical methods using examples and graphics instead. To use the book efficiently, readers should have some computer experience. The book starts with the simplest of statistical concepts and carries readers forward to a deeper and more extensive understanding of the use of statistics in environmental sciences. The book concerns the application of statistical and other computer methods to the management, analysis and display of spatial data. These data are characterised by including locations (geographic coordinates), which leads to the necessity of using maps to display the data and the results of the statistical methods. Although the book uses examples from applied geochemistry, and a large geochemical survey in particular, the principles and ideas equally well apply to other natural sciences, e.g., environmental sciences, pedology, hydrology, geography, forestry, ecology, and health sciences/epidemiology. The book is unique because it supplies direct access to software solutions (based on R, the Open Source version of the S-language for statistics) for applied environmental statistics. For all graphics and tables presented in the book, the R-scripts are provided in the form of executable R-scripts. In addition, a graphical user interface for R, called DAS+R, was developed for convenient, fast and interactive data analysis. Statistical Data Analysis Explained: Applied Environmental Statistics with R provides, on an accompanying website, the software to undertake all the procedures discussed, and the data employed for their description in the book.

Smoothing Techniques

With Implementation in S

Author: Wolfgang Härdle

Publisher: Springer Science & Business Media

ISBN: 1461244323

Category: Mathematics

Page: 262

View: 6962

The author has attempted to present a book that provides a non-technical introduction into the area of non-parametric density and regression function estimation. The application of these methods is discussed in terms of the S computing environment. Smoothing in high dimensions faces the problem of data sparseness. A principal feature of smoothing, the averaging of data points in a prescribed neighborhood, is not really practicable in dimensions greater than three if we have just one hundred data points. Additive models provide a way out of this dilemma; but, for their interactiveness and recursiveness, they require highly effective algorithms. For this purpose, the method of WARPing (Weighted Averaging using Rounded Points) is described in great detail.

S-Plus for the Analysis of Biological Data

Author: Rhondda E. Jones,Robin Gilliver,Simon Robson,Will Edwards

Publisher: N.A

ISBN: 9780987514714

Category: Biometry

Page: N.A

View: 3085

A manual to teach people to use the statistical software package S-Plus and to support the process of learning statistical concepts and methods. It is a useful workbook to accompany The Analysis of Biological Data by Whitlock and Schluter, published by Roberts and Co, Colorado.

Statistics for Environmental Science and Management

Author: Bryan F. J. Manly

Publisher: Chapman and Hall/CRC

ISBN: 9781584880295

Category: Mathematics

Page: 336

View: 4759

The use of appropriate statistical methods is essential when working with environmental data. Yet, many environmental professionals are not statisticians. A ready reference guide to the most common methods used in environmental applications, Statistics for Environmental Science and Management introduces the statistical methods most frequently used by environmental scientists, managers, and students. Using a non-mathematical approach, the author describes techniques such as: environmental monitoring, impact assessment, assessing site reclamation, censored data, and Monte Carlo risk assessment, as well as the key topics of time series and spatial data. The book shows the strengths of different types of conclusions available from statistical analyses. It contains internet sources of information that give readers access to the latest information on specific topics. The author's easy to understand style makes the subject matter accessible to anyone with a rudimentary knowledge of the basics of statistics while emphasizing how the techniques are applied in the environmental field. Clearly and copiously illustrated with line drawings and tables, Statistics for Environmental Science and Management covers all the statistical methods used with environmental applications and is suitable as a text for graduate students in the environmental science area.

Victims of Crime Survey

Author: Statistics South Africa,R. Hirschowitz

Publisher: N.A

ISBN: 9780621288315

Category: Social Science

Page: 82

View: 2192

How Bad Are Bananas?

The Carbon Footprint of Everything

Author: Mike Berners-Lee

Publisher: Greystone Books

ISBN: 1553658329

Category: Science

Page: 256

View: 9202

Part green-lifestyle guide, part popular science, How Bad Are Bananas? is the first book to provide the information we need to make carbon-savvy purchases and informed lifestyle choices and to build carbon considerations into our everyday thinking. The book puts our decisions into perspective with entries for the big things (the World Cup, volcanic eruptions, the Iraq war) as well as the small (email, ironing, a glass of beer). And it covers the range from birth (the carbon footprint of having a child) to death (the carbon impact of cremation). Packed full of surprises — a plastic bag has the smallest footprint of any item listed, while a block of cheese is bad news — the book continuously informs, delights, and engages the reader. Solidly researched and referenced, the easily digestible figures, statistics, charts, and graphs (including a section on the carbon footprint of various foods) will encourage discussion and help people to make up their own minds about their consumer choices.

A Handbook of Statistical Analyses Using S-PLUS

Author: Brian S. Everitt

Publisher: CRC Press

ISBN: 9781420057492

Category: Mathematics

Page: 256

View: 5579

Since the first edition of this book was published, S-PLUS has evolved markedly with new methods of analysis, new graphical procedures, and a convenient graphical user interface (GUI). Today, S-PLUS is the statistical software of choice for many applied researchers in disciplines ranging from finance to medicine. Combining the command line language and GUI of S-PLUS now makes this book even more suitable for inexperienced users, students, and anyone without the time, patience, or background needed to wade through the many more advanced manuals and texts on the market. The second edition of A Handbook of Statistical Analyses Using S-Plus has been completely revised to provide an outstanding introduction to the latest version of this powerful software system. Each chapter focuses on a particular statistical technique, applies it to one or more data sets, and shows how to generate the proposed analyses and graphics using S-PLUS. The author explains S-PLUS functions from both the Windows® and command-line perspectives and clearly demonstrates how to switch between the two. This handbook provides the perfect vehicle for introducing the exciting possibilities S-PLUS, S-PLUS 2000, and S-PLUS 6 hold for data analysis. All of the data sets used in the text, along with script files giving the command language used in each chapter, are available for download from the Internet at http://www.iop.kcl.ac.uk/iop/Departments/BioComp/splus.shtml

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