《生长曲线模型及其统计诊断》介绍生长曲线模型的理论及方法，并着重描述了该模型的统计诊断方法，主要内容包括：模型背景、资料介绍、参数估计理论、似然、诊断及贝尔叶斯诊断等，同时也介绍了大量的统计方法，讲述了生长曲线模型在医学、农业及生物等领域的广泛套用。《生长曲线模型及其统计诊断》适合医学、农业及生物领域内的数据分析者，套用统计工作者及从事统计学研究的人员及研究生参考阅读。
基本介绍
- 书名：生长曲线模型及其统计诊断（英）
- 作者：本社
- ISBN：9787030195326
- 出版社：科学出版社
图书信息
作者：本社编
出版社:科学出版社; 第1版 (2007年8月1日)
丛书名: 数学专着系列(英文版)
精装:387页
正文语种:英语
开本:16
ISBN:9787030195326
条形码:9787030195326
商品尺寸: 23.8 x 17.2 x 2.4 cm
商品重量: 798 g
ASIN:B00127B7JI
定价：￥86.00元
内容提要
This book discusses the theory of agrowth curve model(GCM)with particularemphasisontatisticaldiagnostics,which is mainly base donrecent work on diagnostics made by the authors and the ircollaborators.This book is intended for researchers who are working in the area of theoretical studies related to the GCM as well as multivaria test atistical diagnostics,and for applied statis ticians working in application of the GCM topracticalareas.
编辑推荐
《生长曲线模型及其统计诊断》是由科学出版社出版的。
目录
Preface
Acronyms
Notation
Chapter1Introduction
1.1GeneralRemarks
1.1.1StatisticalDiagnostics
1.1.20utliersandInfluentialObservation
1.2StatisticalDiagnosticsinMultivariateAnalysis
1.2.1MultipleOutliersinMultivariateData
1.2.2Statisticaldiagnosticsinmultivariatemodels
1.3GrowthCurveModel(GCM)
1.3.1ABriefReview
1.3.2CovarianceStructureSelection
1.4Summary
1.4.1StatisticalInference
1.4.2DiagnosticsWithinaIikelihoodFramework
1.4.3DiagnosticsWithinaBayesianFramework
1.5PreliminaryResults
1.5.1MatrixOperationandMatrixDerivative
1.5.2Matrix-variateNormalandtDistributions
1.6FurtherReadings
Chapter2GeneralizedLeastSquareEstimation
2.1GeneralRemarks
2.1.1ModelDefinition
2.1.2PracticalExamples
2.2GeneralizedLeastSquareEstimation
2.2.1GeneralizedLeastSquareEstimate(GLSE)
2.2.2BestLinearUnbiasedEstimate(BLUE)
2.2.3IllustrativeExamples
2.3AdmissibleEstimateofRegressionCoefficient
2.3.1Admissibility
2.3.2NecessaryandSufficientCondition
2.4BibliographicalNotes
Chapter3MaximumLikelihoodEstimation
3.1MaximumLikelihoodEstimation
3.1.1MaximumLikelihoodEstimate(MLE)
3.1.2ExpectationandVariance-covariance
3.1.3IllustrativeExamples
3.2Rao'sSimpleCovarianceStructure(SCS)
3.2.1ConditionThattheMLEIsIdenticaltotheGLSE
3.2.2EstimatesofDispersionComponents
3.2.3IllustrativeExamples
3.3RestrictedMaximumLikelihoodEstimation
3.3.1RestrictedMaximumLikelihood(REMLs)estimate
3.3.2REMLsEstimatesintheGCM
3.3.3IllustrativeExamples
3.4BibliographicalNotes
Chapter4DiscordantOutlierandInfluentialObservation
4.1GeneralRemarks
4.1.1DiscordantOutlier-GeneratingModel
4.1.2InfluentialObservation
4.2DiscordantOutlierDetectionintheGCMwithSCS
4.2.1MultipleIndividualDeletionModel(MIDM)
4.2.2MeanShiftRegressionModel(MSRM)
4.2.3MultipleDiscordantOutlierDetection
4.2.4IllustrativeExamples
4.3InfluentialObservationintheGCMwithSCS
4.3.1GeneralizedCook-typeDistance
4.3.2ConfidenceEllipsoid'sVolume
4.3.3InfluenceAssessmentonLinearCombination
4.3.4IllustrativeExamples
4.4DiscordantOutlierDetectionintheGCMwithUC
4.4.1MultipleIndividualDeletionModel(MIDM)
4.4.2MeanShiftRegressionModel(MSRM)
4.4.3MultipleDiscordantOutlierDetection
4.4.4IllustrativeExamples
……
Chapter5Likelihood-BasedLocalInfluence
Chapter6BayesianInfluenceAssessment
Chapter7BaryesianLocalInfluence
Appendix