应用线性回归模型

所属分类:数学  
出版时间:2005-2   出版时间:蓝色畅想   作者:库特纳   页数:701   字数:1000000  
Tag标签:统计,statistics,金融,计量经济学,统计学,数学  

内容概要

本书从McGrawHill出版公司引进,共分三部分,内容包括:第一部分:简单线性回归:一元预测函数的线性回归,回归影响和相关分析,诊断及补救措施,即时推断和回归分析的其它几个专题,简单线性回归分析中的矩阵方法;第二部分:多元线性回归:多元回归Ⅰ,多元回归2,定性回归模型和定量预测,建立线性回归模型Ⅰ:模型选择及有效性,建立线性回归模型Ⅱ:诊断,建立线性回归模型Ⅲ:补救措施,时间序列数据中的自相关;第三部分:非线性回归:非线性回归和神经网络方法。本书篇幅适中,例子多涉及各个应用领域,在介绍统计思想方面比较突出,光盘数据丰富。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。

书籍目录

PARTONE SIMPLELINEARREGRESSION. Chapter1 LinearRegressionwithOnePredictorVariable  1.1RelationsbetweenVariables  1.2RegressionModelsandTheirUses  1.3SimpleLinearRegressionModelwithDistributionofErrorTermsUnspecified  1.4DataforRegressionAnalysis  1.5OverviewofStepsinRegressionAnalysis  1.6EstimationofRegressionFunction  1.7EstimationofErrorTermsVarianceσ2  1.8NormalErrorRegressionModel Chapter2 InferencesinRegressionandCorrelationAnalysis  2.1InferencesConcerning/β1  2.2InferencesConcerning/β0  2.3SomeConsiderationsonMakingInferencesConcerning/50andβ1  2.4IntervalEstimationofE{Yh}  2.5PredictionofNewObservation  2.6ConfidenceBandforRegressionLine  2.7AnalysisofVarianceApproach  2.8GeneralLinearTestApproach  2.9DescriptiveMeasuresofLinearAssociationbetweenXandY  2.10ConsiderationsinApplyingRegressionAnalysis  2.11NormalCorrelationModels Chapter3 DiagnosticsandRemedialMeasures  3.1DiagnosticsforPredictorVariable  3.2Residuals  3.3DiagnosticsforResiduals  3.4OverviewofTestsInvolvingResiduals  3.5CorrelationTestforNormality  3.6TestsforConstancyofError  3.7FTestforLackofFit  3.8OverviewofRemedialMeasures  3.9Transformations  3.10ExplorationofShapeofRegressionFunction  3.11CaseExample--PlutoniumMeasurement Chapter4 SimultaneousInferencesandOtherTopicsinRegressionAnalysis  4.1JointEstimationofβ0andβ1  4.2SimultaneousEstimationofMeanResponses  4.3SimultaneousPredictionIntervalsforNewObservations  4.4RegressionthroughOrigin  4.5EffectsofMeasurementErrors  4.6InversePredictions  4.7ChoiceofXLevels Chapter5 MatrixApproachtoSimpleLinearRegressionAnalysis  5.1Matrices  5.2MatrixAdditionandSubtraction  5.3MatrixMultiplication  5.4SpecialTypesofMatrices  5.5LinearDependenceandRankofMatrix  5.6InverseofaMatrix  5.7SomeBasicResultsforMatrices  5.8RandomVectorsandMatrices  5.9SimpleLinearRegressionModelinMatrixTerms  5.10LeastSquaresEstimation  5.11FittedValuesandResiduals  5.12AnalysisofVarianceResults  5.13InferencesinRegressionAnalysisPARTTWO MULTIPLELINEARREGRESSION Chapter6MultipleRegressionI Chapter7 MultipleRegressionII Chapter8 RegressionModelsforQuantitativeandQualitativePredictors Chapter9 BuildingtheRegressionModelI:ModelSelectionandValidation Chapter10 BuildingtheRegressionModelII:Diagnostics Chapter11 BuildingtheRegressionModelIII:RemedialMeasures Chapter12 AutocorrelationinTimeSeriesDataPARTTHREENONLINEARREGRESSION Chapter13 IntroductiontoNonlinearRegressionandNeuralNetworks Chapter14 LogisticRegression,PoissonRegression,andGeneralizedLinearModelsAppendixA SomeBasicResultsinProbabilityandStatisticsAppendixB TablesAppendixC DataSetsAppendixD SelectedBibliographyIndex

章节摘录

  The
correlation
test
for
normality
described
in
Chapter
3
carries
forward
directly
to
multipldregression.Tbe
expected
values
of
the
ordered
residuals
under
normality
are
calculatedaccording
to(3.6),and
the
coefIicient
of
correlation
between
the
residuals
and
the
expectedvalues
under
normality
is
then
obtained.Table
B.6
is
employed
to
assess
whether
or
nolthe
magnitude
of
the
correlation
coeIIicient
supports
the
reasonableness
of
the
normalityassumption.  The
Brown-Forsythe
test
statistic(3.9)for
assessing
the
constancy
ofthe
error
variance
canbe
used
readily
in
multiple
regression
when
the
error
variance
increases
or
decreases
withone
of
the
predictor
variables.To
conduct
the
Brown-Forsythe
teSt.we
divide
the
data
seinto
two
groups,as
for
simple
linear
regression,where
one
group
consists
of
cases
whenthe
level
of
the
predictor
variable
is
relatively
low
and
the
other
group
consists
of
case
where
the
level
of
the
predictor
variable
is
relatively
hiRh.The
Brown-Forsy
the
test
the
proceeds
as
for
simple
linear
regression.The
Breusch.Pagan
test(3.1
1)for
constancy
of
the
error
variance
in
multiple
regression
icarded
out
exactly
the
same
as
for
simple
linear
regression
when
the
error
variance
increaseor
decreases
with
one
of
the
predictor
variables.
2.
Research
and
Analysis
(including
site
visit) 
A.
Base
Plan
PreparationB.
Site
Inventory
(Data
Collection)
and
Analysis
(Evaluation)C.
Client
InterviewD.
Program
Development

图书封面

图书标签Tags

统计,statistics,金融,计量经济学,统计学,数学


    应用线性回归模型下载



用户评论 (总计21条)

 
 

  •     比我同学早两年买的同一本书的纸张要差一些。还没仔细看,希望没有其他问题吧。
  •     挺不错的~,期待有不错的效果
  •     跟我们老师那书是一样的,书上介绍很系统
  •     学生用的,值得多翻翻。
  •     当当买书快捷方便,这版讲义好
  •     这本书很好的讲诉了spss应用技巧,送货速度快
  •     对论文写作好,书注重理论应用
  •     还不如看网上的材料好,看后会有“原来如此”的感觉。
  •     质量也可以,还是不一样
  •     我就喜欢步骤比较具体,需要慢慢去读。。
  •     理论性有点强,虽然后来又在网上找到了电子版的、、
  •     软件介绍的很好,是学习统计软件不错的教材
  •     内容挺贴近考试要求的,该书简明扼要、易懂
  •     画风我很喜欢,做数据挖掘的同学一定要看看! 很基础
  •     以前用过SPSS不过还是不怎么懂,真是很不错
  •     我觉得还行,适合初学者学习
  •     不知道怎么样,可惜没时间看
  •     学习SAS的经典书籍,以后肯定时不时要用到的。
  •     学习了,不过分成两本就更好了
  •     人大的统计教材,总是让我想起Tomaso Poggio
  •     但我知道张敏强这版有较多的错误。,对于学医学的专业初学人员很实用
 

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