線性模型（簡體書）

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 acpanying text for courses in other areas. Some of the highlights in this book are as follows.

Preface
1 Introduction
2 LinearModels
2.1 RegressionModelsinEconometrics
2.2 EconometricModels
2.3 TheReducedForm
2.4 TheMultivariateRegressionModel
2.5 TheClassicalMultivariateLinearRegressionModel
2.6 TheGeneralizedLinearRegressionModel
3 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 CensoredRegression
4 TheGeneralizedLinearRegressionModel
4.1 OptimalLinearEstimationofB
4.2 TheAitkenEstimator
4.3 MisspecificationoftheDispersionMatrix
4.4 HeteroscedasticityandAutoregression
5 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 WeakenedLinearRestrictions
6 PredictionProblemsintheGeneralizedRegressionModel
6.1 Introduction
6.2 SomeSimpleLinearModels
6.3 ThePredictionModel
6.4 OptimalHeterogeneousPrediction
6.5 OptimalHomogeneousPrediction
6.6 MDEMatrixComparisonsbetweenOptimalandClassical Predictors
6.7 PredictionRegions
7 SensitivityAnalysis
7.1 Introduction
7.2 PredictionMatrix
7.3 TheEffectofaSingleObservationontheEstimationofPa-rameters
7.4 DiagnosticPlotsforTestingtheModelAssumptions
7.5 MeasuresBasedontheConfidenceEllipsoid
7.6 PartialRegressionPlots
8 AnalysisofInpleteDataSets
8.1 StatisticalAnalysiswithMissingData
8.2 MissingDataintheResponse
8.3 MissingValuesintheX-Matrix
8.4 MaximumLikelihoodEstimatesofMissingValues
8.5 WeightedMixedRegression
9 RobustRegression
9.1 Introduction
9.2 LeastAbsoluteDeviationEstimators--UnivariateCase
……
10 ModelsforBinaryResponseVariables
A MatrixAlgebra
B Tables
References
Index