Applied Linear Statistical Models: Applied Linear Regression Models (5版)
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書名:Applied Linear Statistical Models: Applied Linear Regression Models 5/e
作者:KUTNER
出版社:McGraw-Hill
出版日期:2019/09/00
ISBN:9789863414179
內容簡介
1. Added material on important techniques for data mining, including regression trees and neural network models in Chapters 11 and 13.
2. The Chapter on logistic regression (Chapter 14) has been extensively revised and expanded to include a more thorough treatment of logistic, probit, and complementary log-log models, logistic regression residuals, model selection, model assessment, logistic regression diagnostics, and goodness of fit tests. We have also developed new material on polytomous (multicategory) nominal logistic regression models and polytomous ordinal logistic regression models.
3. We have expanded the discussion of model selection methods and criteria. The Akaike information criterion and Schwarz Bayesian criterion have been added, and a greater emphasis is placed on the use of cross-validation for model selection and validation.
4. New open ended 'Cases' based on data sets from business, health care, and engineering are included. Also, many problem data sets have been updated and expanded.
5. The text includes a CD with all data sets and the Student Solutions manual in PDF. In addition a new supplement, SAS and SPSS Program Solutions by Replogle and Johnson is available for the Fifth Edition.
目錄
PART I: SIMPLE LINEAR REGRESSION
Ch 1 Linear Regression with One Predictor Variable
Ch 2 Inferences in Regression and Correlation Analysis
Ch 3 Diagnostics and Remedial Measures
Ch 4 Simultaneous Inferences and Other Topics in Regression Analysis
Ch 5 Matrix Approach to Simple Linear Regression Analysis
PART II: MULTIPLE LINEAR REGRESSION
Ch 6 Multiple Regression I
Ch 7 Multiple Regression II
Ch 8 Regression Models for Quantitative and Qualitative Predictors
Ch 9 Building the Regression Model I: Model Selection and Validation
Ch10 Building the Regression Model II: Diagnostics
Ch11 Building the Regression Model III: Remedial Measures
Ch12 Autocorrelation in Time Series Data
PART III: NONLINEAR REGRESSION
Ch13 Introduction to Nonlinear Regression and Neural Networks
Ch14 Logistic Regression, Poisson Regression, and Generalized Linear Models
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Applied Linear Regression (4版)
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【簡介】
Praise for the Third Edition
"...this is an excellent book which could easily be used as a course text..."
—International Statistical Institute
The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples.
Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illustrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. While maintaining the accessible appeal of each previous edition,Applied Linear Regression, Fourth Edition features:
Graphical methods stressed in the initial exploratory phase, analysis phase, and summarization phase of an analysis
In-depth coverage of parameter estimates in both simple and complex models, transformations, and regression diagnostics
Newly added material on topics including testing, ANOVA, and variance assumptions
Updated methodology, such as bootstrapping, cross-validation binomial and Poisson regression, and modern model selection methods
Applied Linear Regression, Fourth Edition is an excellent textbook for upper-undergraduate and graduate-level students, as well as an appropriate reference guide for practitioners and applied statisticians in engineering, business administration, economics, and the social sciences.
《應用線性迴歸(第四版)》是對線性迴歸建模的基本理論和方法進行全面更新的書籍。本書展示了線性迴歸分析技術的實際應用,並提供了有趣的真實世界練習和例子。
新版強調了模型建立、參數理解、適配度和可靠性評估以及結論的重要概念,並通過最小二乘迴歸的使用來展示如何開發估計、信賴和測試程序。《應用線性迴歸(第四版)》保持了前幾版易於理解的特點,並新增了以下內容:
- 在分析的初始探索階段、分析階段和總結階段強調了圖形方法。
- 深入探討了簡單和複雜模型中的參數估計、轉換和迴歸診斷。
- 新增了測試、ANOVA和變異假設等主題的材料。
- 更新了方法,如自助法、交叉驗證二項式和泊松迴歸以及現代模型選擇方法。
《應用線性迴歸(第四版)》是一本適合高年級本科生和研究生的優秀教科書,也是工程、工商管理、經濟學和社會科學等應用統計學家和實踐者的參考指南。
【目錄】
1 Scatterplots
2 Simple Linear Regression
3 Multiple Regression
4 Interpretation of Main Effects
5 Complex Regressors
6 Testing and Analysis of Variance
7 Variances
8 Transformations
9 Regression Diagnostics
10 Variable Selection
11 Nonlinear Regression
12 Binomial and Poisson Regression
A.1 Website
A.2 Means, Variances, Covariances and Correlations
A.3 Least Squares for Simple Regression
A.4 Means and Variances of Least Squares Estimates
A.5 Estimating E(Y|X) using a Smoother
A.6 A Brief Introduction to Matrices and Vectors
A.7 Random Vectors
A.8 Least Squares Using Matrices
A.9 The QR factorization
A.10 Spectral Decomposition
A.11 Maximum Likelihood Estimates
A.12 The Box–Cox Method for Transformations
A.13 Case Deletion in Linear Regression
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