rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Nonlinear Regression with R
  name:
    name part: Ritz, Christian.
    role:
      role term: editor.
  name:
    name part: Streibig, Jens Carl.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2008
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 148 p. online resource.
  abstract: 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.
  table of 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.
  note: edited by Christian Ritz, Jens Carl Streibig.
  subject:
    topic: Mathematics
  subject:
    topic: Pharmacology
  subject:
    topic: Epidemiology
  subject:
    topic: Forestry
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Computational intelligence
  subject:
    topic: Mathematics
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Pharmacology/Toxicology
  subject:
    topic: Computational Intelligence
  subject:
    topic: Epidemiology
  subject:
    topic: Forestry
  classification: QA273.A1-274.9
  classification: QA274-274.9
  classification: 519.2
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Use R
  identifier: 9780387096162
  identifier: http://dx.doi.org/10.1007/978-0-387-09616-2
  record info:
    record creation date: 100301
    record change date: 20151204183319.0
    record identifier: 978-0-387-09616-2