| Record ID | marc_columbia/Columbia-extract-20221130-007.mrc:231791247:3036 |
| Source | marc_columbia |
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LEADER: 03036cam a22003854a 4500
001 3231018
005 20221020012923.0
008 010817t20022002nyua b 001 0 eng
010 $a 2001053052
020 $a0387953531 (alk. paper)
035 $a(OCoLC)ocm47831606
035 $9AUK2893CU
035 $a(NNC)3231018
035 $a3231018
040 $aDLC$cDLC$dC#P$dOHX$dOrLoB-B
042 $apcc
050 00 $aQA279$b.G8 2002
072 7 $aQA$2lcco
082 00 $a519.5/38$221
100 1 $aGu, Chong.$0http://id.loc.gov/authorities/names/n2001014665
245 10 $aSmoothing spline ANOVA models /$cChong Gu.
260 $aNew York :$bSpringer,$c[2002], ©2002.
300 $axiii, 289 pages :$billustrations ;$c25 cm.
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
490 1 $aSpringer series in statistics
504 $aIncludes bibliographical references (p. [261]-271) and indexes.
505 00 $g1.$tIntroduction.$g1.1.$tEstimation Problem and Method.$g1.2.$tNotation.$g1.3.$tDecomposition of Multivariate Functions.$g1.4.$tCase Studies.$g1.5.$tScope --$g2.$tModel Construction.$g2.1.$tReproducing Kernel Hilbert Spaces.$g2.2.$tSmoothing Splines on {1, ...,K}.$g2.3.$tPolynomial Smoothing Splines on [0,1].$g2.4.$tSmoothing Splines on Product Domains.$g2.5.$tBayes Model.$g2.6.$tMinimization of Penalized Functional --$g3.$tRegression with Gaussian-Type Responses.$g3.1.$tPreliminaries.$g3.2.$tSmoothing Parameter Selection.$g3.3.$tBayesian Confidence Intervals.$g3.4.$tComputation: Generic Algorithms.$g3.5.$tSoftware.$g3.6.$tModel Checking Tools.$g3.7.$tCase Studies.$g3.8.$tComputation: Special Algorithms --$g4.$tMore Splines.$g4.1.$tPartial Splines.$g4.2.$tSplines on the Circle.$g4.3.$tL-Splines.$g4.4.$tThin-Plate Splines --$g5.$tRegression with Exponential Families.$g5.1.$tPreliminaries.$g5.2.$tSmoothing Parameter Selection.$g5.3.$tApproximate Bayesian Confidence Intervals.
505 80 $g5.4.$tSoftware: R Package gss.$g5.5.$tCase Studies --$g6.$tProbability Density Estimation.$g6.1.$tPreliminaries.$g6.2.$tPoisson Intensity.$g6.3.$tSmoothing Parameter Selection.$g6.4.$tComputation.$g6.5.$tCase Studies.$g6.6.$tBiased Sampling and Random Truncation.$g6.7.$tConditional Densities.$g6.8.$tResponse-Based Sampling --$g7.$tHazard Rate Estimation.$g7.1.$tPreliminaries.$g7.2.$tSmoothing Parameter Selection.$g7.3.$tCase Studies.$g7.4.$tPenalized Partial Likelihood.$g7.5.$tModels Parametric in Time --$g8.$tAsymptotic Convergence.$g8.1.$tPreliminaries.$g8.2.$tRates for Density Estimates.$g8.3.$tRates for Hazard Estimates.$g8.4.$tRates for Regression Estimates.
650 0 $aAnalysis of variance.$0http://id.loc.gov/authorities/subjects/sh85004782
650 0 $aSpline theory.$0http://id.loc.gov/authorities/subjects/sh85126830
650 0 $aSmoothing (Statistics)$0http://id.loc.gov/authorities/subjects/sh85123709
830 0 $aSpringer series in statistics.$0http://id.loc.gov/authorities/names/n42023188
852 00 $bmat$hQA279$i.G8 2002
852 00 $bmat$hQA279$i.G8 2002