经典和现代回归分析及其应用

出版时间：2008-1  出版社：高等教育  作者：[美] 麦尔斯  页数：488  
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前言

No single statistical tool has received the attention given to regression analysisin the past 25 years. Both practical data analysts and statistical theorists have con-tributed to an unprecedented advancement in this important and dynamic topic.Many volumes have been written by statisticians and scientists with the resultbeing that the arsenal of effective regression methods has increased manyfold.　My intent for this second edition is to provide a rather substantial increase inmaterial related to classical regression while continuing to introduce relevant newand modern techniques. I have included major supplements in simple linearregression that deal with simultaneous influence, maximum likelihood estimationof parameters, and the plotting of residuals. In multiple regression, new andsubstantial sections on the use of the general linear hypothesis, indicator variables,the geometry of least squares, and relationship to ANOVA models are added. Inaddition, all new topics are illustrated with the use of real-life data sets andannotated computer printout. In the area of useful modern techniques, additionaltypes of diagnostic residual plots are developed and illustrated, including compo-nent plus residual plots and augmented partial plots. These plots are designedto provide a two-dimensional picture of the role of each regressor in the multipleregression and graphically highlight the need for nonlinearities in the regressionmodel.

内容概要

本书从ThomsonLearning出版公司引进，本书内容包括：回归分析，简单线性回归模型，多元线性回归模型，最佳模型的标准选择，残差分析，影响诊断，非标准条件、假设和转换，检测及多元共线性，非线性回归，附录A：矩阵代数中的一些概念，附录B：一些处理方法。本书适用于高等院校统计学专业和理工科各专业本科生和研究生作为教材使用。　　通过影印、翻译、编译这批优秀教材的长处，吸取国外出版公司的制作经验，提升我们自编教材的教学资源配套标准，使我国高校教材建设水平上一个新的台阶：与此同时，我们还将尝试组织海外作者和国内作者合编外文版基础课数学教材，并约请国内专家改编部分国外优秀教材，以适应我国实际教学环境。

作者简介

作者：（美国）麦尔斯（Myers.R.H）

书籍目录

CHAPTER1　INTRODUCTION:REGRESSIONANALYSIS　1.1　Regressionmodels　1.2　Formalusesofregressionanalysis　1.3　Thedatabase　ReferencesCHAPTER2　THESIMPLELINEARREGRESSIONMODEL　2.1　Themodeldescription　2.2　Assumptionsandinterpretationofmodelparameters　2.3　Leastsquaresformulation　2.4　Maximumlikelihoodestimation　2.5　Partioningtotalvariability　2.6　Testsofhypothesisonslopeandintercept　2.7　Simpleregressionthroughtheorigin（Fixedintercept）　2.8　Qualityoffittedmodel　2.9　Confidenceintervalsonmeanresponseandpredictionintervals　2.10　Simultaneousinferenceinsimplelinearregression　2.11　Acompleteannotatedcomputerprintout　2.12　Alookatresiduals　2.13　Bothxandyrandom　Exercises　ReferencesCHAPTER3　THEMULTIPLELINEARREGRESSIONMODEL　3.1　Modeldescriptionandassumptions　3.2　Thegenerallinearmodelandtheleastsquaresprocedure　3.3　Propertiesofleastsquaresestimatorsunderidealconditions　3.4　Hypothesistestinginmultiplelinearregression　3.5　Confidenceintervalsandpredictionintervalsinmultipleregressions　3.6　Datawithrepeatedobservations　3.7　Simultaneousinferenceinmultipleregression　3.8　Multicollinearityinmultipleregressiondata　3.9　Qualityfit,qualityprediction,andtheHATmatrix　3.10　Categoricalorindicatorvariables（RegressionmodelsandANOVAmodems）ExercisesReferencesCHAPTER4　CRITERIAFORCHOICEOFBESTMODEL　4.1　Standardcriteriaforcomparingmodels　4.2　Crossvalidationformodelselectionanddeterminationofmodelperformance　4.3　Conceptualpredictivecriteria（TheCp=statistic）　4.4　Sequentialvariableselectionprocedures　4.5　FurthercommentsandallpossibleregressionsExercisesReferencesCHAPTER5　ANALYSISOFRESIDUALS　5.1　Informationretrievedfromresiduals　5.2　Plottingofresiduals　5.3　Studentizedresiduals　5.4　RelationtostandardizedPRESSresiduals　5.5　Detectionofoutliers　5.6　Diagnosticplots　5.7　Normalresidualplots　5.8　Furthercommentsonanalysisofresiduals　Exercises　ReferencesCHAPTER6　INFLUENCEDIAGNOSTICS　6.1　Sourcesofinfluence　6.2　Diagnostics:ResidualsandtheHATmatrix　6.3　Diagnosticsthatdetermineextentofinfluence　6.4　Influenceonperformance　6.5　Whatdowedowithhighinfluencepoints?ExercisesReferencesCHAPTER7　NONSTANDARDCONDITIONS,VIOLATIONSOFASSUMPTIONS,ANDTRANSFORMATIONS　7.1　Heterogeneousvariance:Weightedleastsquares　7.2　Problemwithcorrelatederrors（Autocorrelation）　7.3　Transformationstoimprovefitandprediction　7.4　Regressionwithabinaryresponse　7.5　Furtherdevelopmentsinmodelswithadiscreteresponse（Poissonregression）　7.6　Generalizedlinearmodels　7.7　Failureofnormalityassumption:Presenceofoutliers　7.8　MeasurementerrorsintheregressorvariablesExercisesReferencesCHAPTER8　DETECTINGANDCOMBATINGMULTICOLLINEARITYCHAPTER9　NONLINEARREGRESSIONAPPENDIXA　SOMESPECIALCONCEPTSINMATRIXALGEBRAAPPENDIXB　SOMESPECIALMANIPULATIONSReferencesAPPENDIXCSTATISTICALTABLESINDEX

章节摘录

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用户评论 (总计13条)

•   如果真想好好研究一番回归理论的话，这是一本不可多得的好书，我读过国内好几本讲回归的比较出名的书，但是都没有这本书讲的详细
•   这本书是学回归分析一本很好的书！可惜为什么总是缺货呢？！
•   原版书太贵，只好选择影印版，质量也很不错！
•   这本书超漂亮的，看上去就很值钱的那种啊
•   well-writtenandstandardtextbookstyle
•   讲得很清楚，老美的教材就是好
•   是比较基础的一本书，虽然没有全部看完，不过个人觉得还可以，只是从作者的角度，有些特定语句表述与其他作者的有所差别！
•   这是英文版，质量还可以，老师发的链接让买的，内容估计也行
•   一般的文科生是看不懂的
•   这本书内容写的很不错，适合初学者学习，英语通俗易懂！
•   适合本科高年级学生使用
•   正在看，讲解很清楚，用的词也很简单易懂，不用担心英文基础。等到读完再来评价。
•   就是英文的 要是中文的更好了