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: Spatial Predictive Modeling with R
  name:
    name part: Li, Jin.
    role:
      role term: creator
  name:
    name part: ProQuest (Firm)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2022
    copyright date: 2022
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource ( 416 pages) :
  table of contents: 1. Data acquisition, data quality control and spatial reference systems2. Predictive variables and exploratory analysis3. Model evaluation and validation4. Mathematical spatial interpolation methods5. Univariate geostatistical methods6. Multivariate geostatistical methods7. Modern statistical methods8. Tree-based machine learning methods9. Support vector machine10. Hybrids of modern statistical methods with mathematical and univariate geostatistical methods11. Hybrids of machine learning methods with mathematical and univariate geostatistical methods12. Applications and comparisons of spatial predictive methodsAppendix A. Data sets used in this book
  note: Jin Li.
  note: Dr Jin Li works at Data2action, Australia as a Founder. He has research experience in spatial predictive modelling, statistical computing, ecological and environmental modelling, and ecology. As a scientist, he worked in the Chinese Academy of Sciences, University of New England, CSIRO, and Geoscience Australia. He was an Associate Editor (Jul 2008-Dec 2015) and an editorial board member (Jan 2016-April 2020) of Acta Oecologica, and a Guest Academic Editor (Mar 2018) and an Academic Editor (May 2018-Apr 2020) of PLOS ONE. He has produced over 100 various publications, developed a number of hybrid methods for spatial predictive modeling, and published four R packages for variable selections and spatial predictive modelling. For further information see https://www.researchgate.net/profile/Jin-Li-74, https://scholar.google.com/citations?user=Jeot53EAAAAJ&hl=en and https://www.linkedin.com/in/jin-li-01421a68.
  note: Includes bibliographical references and index.
  subject:
    topic: Computer simulation
  subject:
    topic: R (Computer program language)
  subject:
    topic: Computer Simulation
  subject:
    topic: Simulation par ordinateur
  subject:
    topic: R (Langage de programmation)
  subject:
    topic: simulation
  subject:
    topic: MATHEMATICS
    topic: Probability & Statistics
    topic: Regression Analysis
  subject:
    topic: Computer simulation
  subject:
    topic: R (Computer program language)
  classification: QA76.9.C65 L52 2022
  classification: 003.3
  identifier: 9781003091776
  identifier: 1003091776
  identifier: 9781000542639
  identifier: 1000542637
  identifier: 9781000542608
  identifier: 1000542602
  identifier: 9780367550547
  identifier: 9780367550561
  identifier: 9781003091776 Taylor & Francis
  identifier: https://ebookcentral.proquest.com/lib/tamucs/detail.action
  record info:
    record content source: TYFRS
    record creation date: 211007
    record change date: 20220721135500.3
    record identifier: in00004585930
    language of cataloging:
      language term: eng