质能均衡：化工计算（1982年第四版）

Preface
1.Introduction
1.1SmoothingMethods:aNonparametric/Parametric
Compromise
1.2UsesofSmoothingMethods
1.3OutlineoftheChapters
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Computationalissues
Exercises
2.SimpleUnivariateDensityEstimation
2.1TheHistogram
2.2TheFrequencyPolygon
2.3VaryingtheBinWidth
2.4TheEffectivenessofSimpleDensityEstimators
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Computationalissues
Exercises
3.SmootherUnivariateDensityEstimation
3.1KernelDensityEstimation
3.2ProblemswithKernelDensityEstimation
3.3AdjustmentsandImprovementstoKernelDensityEstimation
3.4LocalLikelihoodEstimation
3.5RoughnessPenaltyandSpline-BasedMethods
3.6ComparisonofUnivariateDensityEstimators
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Computationalissues
Exercises
4.MultivariateDensityEstimation
4.1SimpleDensityEstimationMethods
4.2KernelDensityEstimation
4.3OtherEstimators
4.4DimensionReductionandProjectionPursuit
4.5TheStateofMultivariateDensityEstimation
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Computationalissues
Exercises
5.NonparametricRegression
5.1ScatterPlotSmoothingandKernelRegression
5.2LocalPolynomialRegression
5.3BandwidthSelection
5.4LocallyVaryingtheBandwidth
5.5OutliersandAutocorrelation
5.6SplineSmoothing
5.7MultiplePredictorsandAdditiveModels
5.8ComparingNonparametricRegressionMethods
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Computationalissues
Exercises
6.SmoothingOrderedCategoricalData
6.1SmoothingandOrderedCategoricalData
6.2SmoothingSparseMultinomiats
6.3SmoothingSparseContingencyTables
6.4CategoricalData,Regression,andDensityEstimation
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Computationalissues
Exercises
7.FurtherApplicationsofSmoothing
7.1DiscriminantAnalysis
7.2Goodness-of-FitTests
7.3Smoothing-BasedParametricEstimation
7.4TheSmoothedBootstrap
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Computationalissues
Exercises
Appendices
A.DescriptionsoftheDataSets
B.MoreonComputationalIssues
References
AuthorIndex
SubjectIndex