线性模型
1998-8
世界图书出版公司
C.R.Rao/等
35
The book is based on both authors' several years of experience in teaching linear models at various levels. It gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in other areas. Some of the highlights in this book are as follows.
Preface1 Introduction2 LinearModels 2.1 RegressionModelsinEconometrics 2.2 EconometricModels 2.3 TheReducedForm 2.4 TheMultivariateRegressionModel 2.5 TheClassicalMultivariateLinearRegressionModel 2.6 TheGeneralizedLinearRegressionModel3 TheLinearRegressionModel 3.1 TheLinearModel 3.2 ThePrincipleofOrdinaryLeastSquares(OLS) 3.3 GeometricPropertiesofOLS 3.4 BestLinearUnbiasedEstimation 3.5 Estimation(Prediction)oftheErrorTermeand2 3.6 ClassicalRegressionunderNormalErrors 3.7 TestingLinearHypotheses 3.8 AnalysisofVarianceandGoodnessofFit 3.9 TheCanonicalForm 3.10 MethodsforDealingwithMulticollinearity 3.11 ProjectionPursuitRegression 3.12 TotalLeastSquares 3.13 MinimaxEstimation 3.14 CensoredRegression4 TheGeneralizedLinearRegressionModel 4.1 OptimalLinearEstimationofB 4.2 TheAitkenEstimator 4.3 MisspecificationoftheDispersionMatrix 4.4 HeteroscedasticityandAutoregression5 ExactandStochasticLinearRestrictions 5.1 UseofPriorInformation 5.2 TheRestrictedLeast-SquaresEstimator 5.3 StepwiseInclusionofExactLinearRestrictions 5.4 BiasedLinearRestrictionsandMDEComparisonwiththeOLSE 5.5 MDEMatrixComparisonsofTwoBiasedEstimators 5.6 MDEMatrixComparisonofTwoLinearBiasedEstimators 5.7 MDEComparisonofTwo(Biased)RestrictedEstimators 5.8 StochasticLinearRestrictions 5.9 WeakenedLinearRestrictions6 PredictionProblemsintheGeneralizedRegressionModel 6.1 Introduction 6.2 SomeSimpleLinearModels 6.3 ThePredictionModel 6.4 OptimalHeterogeneousPrediction 6.5 OptimalHomogeneousPrediction 6.6 MDEMatrixComparisonsbetweenOptimalandClassical Predictors 6.7 PredictionRegions7 SensitivityAnalysis 7.1 Introduction 7.2 PredictionMatrix 7.3 TheEffectofaSingleObservationontheEstimationofPa-rameters 7.4 DiagnosticPlotsforTestingtheModelAssumptions 7.5 MeasuresBasedontheConfidenceEllipsoid 7.6 PartialRegressionPlots8 AnalysisofIncompleteDataSets 8.1 StatisticalAnalysiswithMissingData 8.2 MissingDataintheResponse 8.3 MissingValuesintheX-Matrix 8.4 MaximumLikelihoodEstimatesofMissingValues 8.5 WeightedMixedRegression9 RobustRegression 9.1 Introduction 9.2 LeastAbsoluteDeviationEstimators--UnivariateCase ……10 ModelsforBinaryResponseVariablesA MatrixAlgebraB TablesReferencesIndex
