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  <titleInfo>
    <title>Bayesian smoothing and regression for longitudinal, spatial and event history data</title>
  </titleInfo>
  <name type="personal">
    <namePart>Fahrmeir, L.</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
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  <name type="personal">
    <namePart>Kneib, Thomas.</namePart>
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    <place>
      <placeTerm type="text">Oxford</placeTerm>
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    <publisher>Oxford University Press</publisher>
    <dateIssued>2011</dateIssued>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
    <form authority="gmd">electronic resource</form>
    <extent>1 online resource (xviii, 521 p.) : ill., maps.</extent>
  </physicalDescription>
  <abstract>Bringing together recent advances in smoothing and semiparametric regression from a Bayesian perspective, this book demonstrates, with worked examples, the application of these statistical methods to a variety of fields including forestry development economics, medicine and marketing.</abstract>
  <targetAudience authority="marctarget">specialized</targetAudience>
  <note type="statement of responsibility">Ludwig Fahrmeir, Thomas Kneib.</note>
  <note>Includes bibliographical references and index.</note>
  <subject authority="lcsh">
    <topic>Regression analysis</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Bayesian statistical decision theory</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Smoothing (Statistics)</topic>
  </subject>
  <classification authority="lcc">QA278.2</classification>
  <classification authority="ddc" edition="23">519.536</classification>
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  <relatedItem type="series">
    <titleInfo>
      <title>Oxford statistical science series ; no. 36</title>
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  <identifier type="isbn">9780191728501 (ebook) :</identifier>
  <identifier type="uri">http://dx.doi.org/10.1093/acprof:oso/9780199533022.001.0001</identifier>
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    <url displayLabel="Oxford scholarship online">http://dx.doi.org/10.1093/acprof:oso/9780199533022.001.0001</url>
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