The Resource Nonlinear regression with R, Christian Ritz, Jens Carl Streibig
Nonlinear regression with R, Christian Ritz, Jens Carl Streibig
Resource Information
The item Nonlinear regression with R, Christian Ritz, Jens Carl Streibig represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.This item is available to borrow from 1 library branch.
Resource Information
The item Nonlinear regression with R, Christian Ritz, Jens Carl Streibig represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.
This item is available to borrow from 1 library branch.
- Summary
- R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. Currently, R offers a wide range of functionality for nonlinear regression analysis, but the relevant functions, packages and documentation are scattered across the R environment. This book provides a coherent and unified treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology. The book begins with an introduction on how to fit nonlinear regression models in R. Subsequent chapters explain in more depth the salient features of the fitting function nls(), the use of model diagnostics, the remedies for various model departures, and how to do hypothesis testing. In the final chapter grouped-data structures, including an example of a nonlinear mixed-effects regression model, are considered. Christian Ritz has a PhD in biostatistics from the Royal Veterinary and Agricultural University. For the last 5 years he has been working extensively with various applications of nonlinear regression in the life sciences and related disciplines, authoring several R packages and papers on this topic. He is currently doing postdoctoral research at the University of Copenhagen. Jens C. Streibig is a professor in Weed Science at the University of Copenhagen. He has for more than 25 years worked on selectivity of herbicides and more recently on the ecotoxicology of pesticides and has extensive experience in applying nonlinear regression models. Together with the first author he has developed short courses on the subject of this book for students in the life sciences
- Language
- eng
- Extent
- 1 online resource (xi, 144 pages)
- Contents
-
- Getting Started
- Starting Values and Self-starters
- More on nls()
- Model Diagnostics
- Remedies for Model Violations
- Uncertainty, Hypothesis Testing, and Model Selection
- Grouped Data
- Isbn
- 9780387096162
- Label
- Nonlinear regression with R
- Title
- Nonlinear regression with R
- Statement of responsibility
- Christian Ritz, Jens Carl Streibig
- Subject
-
- Nonlinear theories
- Nonlinear theories
- Nonlinear theories
- Nonlinear theories
- R (Computer program language)
- R (Computer program language)
- R (Computer program language)
- R (Computer program language)
- Regression analysis -- Data processing
- Regression analysis -- Data processing
- Regression analysis -- Data processing
- Regression analysis -- Data processing
- MATHEMATICS -- Probability & Statistics | Regression Analysis
- Language
- eng
- Summary
- R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. Currently, R offers a wide range of functionality for nonlinear regression analysis, but the relevant functions, packages and documentation are scattered across the R environment. This book provides a coherent and unified treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology. The book begins with an introduction on how to fit nonlinear regression models in R. Subsequent chapters explain in more depth the salient features of the fitting function nls(), the use of model diagnostics, the remedies for various model departures, and how to do hypothesis testing. In the final chapter grouped-data structures, including an example of a nonlinear mixed-effects regression model, are considered. Christian Ritz has a PhD in biostatistics from the Royal Veterinary and Agricultural University. For the last 5 years he has been working extensively with various applications of nonlinear regression in the life sciences and related disciplines, authoring several R packages and papers on this topic. He is currently doing postdoctoral research at the University of Copenhagen. Jens C. Streibig is a professor in Weed Science at the University of Copenhagen. He has for more than 25 years worked on selectivity of herbicides and more recently on the ecotoxicology of pesticides and has extensive experience in applying nonlinear regression models. Together with the first author he has developed short courses on the subject of this book for students in the life sciences
- Cataloging source
- GW5XE
- http://library.link/vocab/creatorName
- Ritz, Christian
- Dewey number
- 519.5360285
- Illustrations
- illustrations
- Index
- index present
- LC call number
- QA278.2
- LC item number
- .R58 2008eb
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- bibliography
- http://library.link/vocab/relatedWorkOrContributorName
- Streibig, Jens C
- Series statement
- Use R!
- http://library.link/vocab/subjectName
-
- Regression analysis
- Nonlinear theories
- R (Computer program language)
- MATHEMATICS
- R (Computer program language)
- Regression analysis
- Nonlinear theories
- Nonlinear theories
- R (Computer program language)
- Regression analysis
- Label
- Nonlinear regression with R, Christian Ritz, Jens Carl Streibig
- Bibliography note
- Includes bibliographical references and index
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- multicolored
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Getting Started -- Starting Values and Self-starters -- More on nls() -- Model Diagnostics -- Remedies for Model Violations -- Uncertainty, Hypothesis Testing, and Model Selection -- Grouped Data
- Control code
- 314175017
- Dimensions
- unknown
- Extent
- 1 online resource (xi, 144 pages)
- Form of item
- online
- Isbn
- 9780387096162
- Lccn
- 2008938643
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations.
- http://library.link/vocab/ext/overdrive/overdriveId
- 978-0-387-09615-5
- Specific material designation
- remote
- System control number
- (OCoLC)314175017
- Label
- Nonlinear regression with R, Christian Ritz, Jens Carl Streibig
- Bibliography note
- Includes bibliographical references and index
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- multicolored
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Getting Started -- Starting Values and Self-starters -- More on nls() -- Model Diagnostics -- Remedies for Model Violations -- Uncertainty, Hypothesis Testing, and Model Selection -- Grouped Data
- Control code
- 314175017
- Dimensions
- unknown
- Extent
- 1 online resource (xi, 144 pages)
- Form of item
- online
- Isbn
- 9780387096162
- Lccn
- 2008938643
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations.
- http://library.link/vocab/ext/overdrive/overdriveId
- 978-0-387-09615-5
- Specific material designation
- remote
- System control number
- (OCoLC)314175017
Subject
- Nonlinear theories
- Nonlinear theories
- Nonlinear theories
- Nonlinear theories
- R (Computer program language)
- R (Computer program language)
- R (Computer program language)
- R (Computer program language)
- Regression analysis -- Data processing
- Regression analysis -- Data processing
- Regression analysis -- Data processing
- Regression analysis -- Data processing
- MATHEMATICS -- Probability & Statistics | Regression Analysis
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.library.missouri.edu/portal/Nonlinear-regression-with-R-Christian-Ritz-Jens/zi0YQgGCFHE/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.missouri.edu/portal/Nonlinear-regression-with-R-Christian-Ritz-Jens/zi0YQgGCFHE/">Nonlinear regression with R, Christian Ritz, Jens Carl Streibig</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.missouri.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.missouri.edu/">University of Missouri Libraries</a></span></span></span></span></div>
