MARC Record from marc_columbia

LEADER: 04219cam a2200757 i 4500
001 15100608
005 20220604233156.0
006 m o d
007 cr cnu---unuuu
008 140711s1994 enka ob 001 0 eng d
035 $a(OCoLC)ocn883391217
035 $a(NNC)15100608
040 $aGW5XE$beng$erda$epn$cGW5XE$dOCLCQ$dOCLCO$dYDX$dOCLCQ$dUKAHL$dK6U$dOCLCO$dSFB$dOCLCO$dOCLCQ$dOCLCO
019 $a1260359189
020 $a9781489944733$q(electronic bk.)
020 $a1489944737$q(electronic bk.)
020 $a9780429161056$q(electronic bk.)
020 $a0429161050$q(electronic bk.)
020 $z0412300400
020 $z9780412300400
024 7 $a10.1007/978-1-4899-4473-3$2doi
035 $a(OCoLC)883391217$z(OCoLC)1260359189
050 4 $aQA278.2$b.G735 1994eb
082 04 $a519.5/36$222
084 $a31.73$2bcl
084 $aQH 234$2rvk
084 $aSK 840$2rvk
049 $aZCUA
100 1 $aGreen, P. J.$q(Peter J.)
245 10 $aNonparametric regression and generalized linear models :$ba roughness penalty approach /$cP.J. Green and B.W. Silverman.
250 $aFirst edition.
264 1 $aLondon ;$aNew York :$bChapman & Hall,$c1994.
300 $a1 online resource (ix, 182 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aMonographs on statistics and applied probability ;$v58
504 $aIncludes bibliographical references (pages 169-173) and indexes.
588 0 $aPrint version record.
505 0 $a1. Introduction -- 2. Interpolating and smoothing splines -- 3. One-dimensional case: further topics -- 4. Partial splines -- 5. Generalized linear models -- 6. Extending the model -- 7. Thin plate splines -- 8. Available software.
520 1 $a"Over the past 15 years there has been a great deal of interest and activity in the general area of nonparametric smoothing in statistics. This monograph concentrates on the roughness penalty method with the aim of showing how it provides a unifying approach to a wide range of smoothing problems. The method allows parametric assumptions to be relaxed both in regression problems and in those approached by generalized linear modelling." "The emphasis throughout is methodological rather than theoretical and concentrates on statistical and computational issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. Some publicly available software is also discussed. The mathematical treatment is intended to be largely self-contained, and depends mainly on simple linear algebra and calculus." "This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students and others encountering the material for the first time."--Jacket
650 0 $aRegression analysis.
650 0 $aNonparametric statistics.
650 1 $aNonparametric statistics.
650 02 $aRegression Analysis
650 2 $aStatistics, Nonparametric
650 6 $aAnalyse de régression.
650 6 $aStatistique non paramétrique.
650 7 $aMéthodes statistiques.$2eclas
650 7 $aAnalyse statistique.$2eclas
650 7 $aNonparametric statistics.$2fast$0(OCoLC)fst01038853
650 7 $aRegression analysis.$2fast$0(OCoLC)fst01432090
650 7 $aLineare Regression$2gnd
650 7 $aLineares Regressionsmodell$2gnd
650 7 $aNichtparametrisches Verfahren$2gnd
650 17 $aRegressieanalyse.$2gtt
650 17 $aLineaire modellen.$2gtt
650 17 $aNon-parametrische statistiek.$2gtt
650 7 $aAnalyse de régression.$2ram
650 7 $aStatistique non-paramétrique.$2ram
655 4 $aElectronic books.
700 1 $aSilverman, B. W.,$d1952-
776 08 $iPrint version:$aGreen, P.J. (Peter J.).$tNonparametric regression and generalized linear models.$bFirst edition$z0412300400$w(DLC) 93074213$w(OCoLC)29635089
830 0 $aMonographs on statistics and applied probability (Series) ;$v58.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15100608$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS