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EBOOKCENTRAL_on1347029371 |
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20240329122006.0 |
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230209s2013 xx o ||| 0 eng d |
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|a EBLCP
|b eng
|c EBLCP
|d OCLCQ
|d EBLCP
|d OCLCQ
|d OCLCO
|d OCLCQ
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|a 9781118593042
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|a 1118593049
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|a (OCoLC)1347029371
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|a 519.5/36
|q OCoLC
|2 23/eng/20230216
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049 |
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|a UAMI
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100 |
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|a Hocking, Ronald R.
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245 |
1 |
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|a Methods and Applications of Linear Models
|h [electronic resource] :
|b Regression and the Analysis of Variance.
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260 |
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|a Newark :
|b John Wiley & Sons, Incorporated,
|c 2013.
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300 |
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|a 1 online resource (717 p.).
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490 |
1 |
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|a New York Academy of Sciences Ser.
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500 |
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|a Description based upon print version of record.
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|a Intro -- Methods and Applications of Linear Models -- Contents -- Preface to the Third Edition -- Preface to the Second Edition -- Preface to the First Edition -- PART I REGRESSION -- 1 Introduction to Linear Models -- 1.1 Background Information -- 1.2 Mathematical and Statistical Models -- 1.3 Definition of the Linear Model -- 1.4 Examples of Regression Models -- 1.4.1 Single-Variable, Regression Model -- 1.4.2 Regression Models with Several Inputs -- 1.4.3 Discrete Response Variables -- 1.4.4 Multivariate Linear Models -- 1.5 Concluding Comments -- Exercises
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|a 2 Regression on Functions of One Variable -- 2.1 The Simple Linear Regression Model -- 2.2 Parameter Estimation -- 2.2.1 Least Squares Estimation -- 2.2.2 Maximum Likelihood Estimation -- 2.2.3 Coded Data: Centering and Scaling -- 2.2.4 The Analysis of Variance Table -- 2.3 Properties of the Estimators and Test Statistics -- 2.3.1 Moments of Linear Functions of Random Variables -- 2.3.2 Moments of Least Squares Estimators -- 2.3.3 Distribution of the Least Squares Estimators -- 2.3.4 The Distribution of Test Statistics -- 2.4 The Analysis of Simple Linear Regression Models
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|a 2.4.1 Two Numerical Examples -- 2.4.2 A Test for Lack-of-Fit -- 2.4.3 Inference on the Parameters of the Model -- 2.4.4 Prediction and Prediction Intervals -- 2.5 Examining the Data and the Model -- 2.5.1 Residuals -- 2.5.2 Outliers, Extreme Points, and Influence -- 2.5.3 Normality, Independence, and Variance Homogeneity -- 2.6 Polynomial Regression Models -- 2.6.1 The Quadratic Model -- 2.6.2 Higher Ordered Polynomial Models -- 2.6.3 Orthogonal Polynomials -- 2.6.4 Regression through the Origin -- Exercises -- 3 Transforming the Data -- 3.1 The Need for Transformations
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|a 3.2 Weighted Least Squares -- 3.3 Variance Stabilizing Transformations -- 3.4 Transformations to Achieve a Linear Model -- 3.4.1 Transforming the Dependent Variable -- 3.4.2 Transforming the Predictors -- 3.5 Analysis of the Transformed Model -- 3.5.1 Transformations with Forbes Data -- Exercises -- 4 Regression on Functions of Several Variables -- 4.1 The Multiple Linear Regression Model -- 4.2 Preliminary Data Analysis -- 4.3 Analysis of the Multiple Linear Regression Model -- 4.3.1 Fitting the Model in Centered Form -- 4.3.2 Estimation and Analysis of the Original Data
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|a 4.3.3 Model Assessment and Residual Analysis -- 4.3.4 Prediction -- 4.3.5 Transforming the Response -- 4.4 Partial Correlation and Added-Variable Plots -- 4.4.1 Partial Correlation -- 4.4.2 Added-Variable Plots -- 4.4.3 Simple Versus Partial Correlation -- 4.5 Variable Selection -- 4.5.1 The Case of Orthogonal Predictors -- 4.5.2 Criteria for Deletion of Variables -- 4.5.3 Nonorthogonal Predictors -- 4.5.4 Computational Considerations -- 4.5.5 Selection Strategies -- 4.6 Model Specification -- 4.6.1 Application to Subset Selection -- 4.6.2 Improved Mean Squared Error
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|a 4.6.3 Development of the Cp Statistic
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590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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655 |
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0 |
|a Electronic books.
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776 |
0 |
8 |
|i Print version:
|a Hocking, Ronald R.
|t Methods and Applications of Linear Models
|d Newark : John Wiley & Sons, Incorporated,c2013
|z 9781118329504
|
830 |
|
0 |
|a New York Academy of Sciences Ser.
|
856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=7103839
|z Texto completo
|
938 |
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|a ProQuest Ebook Central
|b EBLB
|n EBL7103839
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994 |
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|a 92
|b IZTAP
|