线性模型

出版时间：1998-8  出版社：世界图书出版公司  作者：C.R.Rao/等  页数：35  

内容概要

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.

书籍目录

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