经典和现代回归分析及其应用 第2版PDF格式文档图书下载
- 购买点数:15 点
- 作 者:(美)麦尔斯(Myers R.H.)著
- 出 版 社:北京:高等教育出版社
- 出版年份:2005
- ISBN:7040163233
- 标注页数:489 页
- PDF页数:501 页
CHAPTER 1 INTRODUCTION:REGRESSION ANALYSIS 1
1.1 Regression models 3
1.2 Formal uses of regression analysis 5
1.3 The data base 6
References 7
CHAPTER 2 THE SIMPLE LINEAR REGRESSION MODEL 8
2.1 The model description 8
2.2 Assumptions and interpretation of model parameters 9
2.3 Least squares formulation 12
2.4 Maximum likelihood estimation 20
2.5 Partioning total variability 22
2.6 Tests of hypothesis on slope and intercept 26
2.7 Simple regression through the origin(Fixed intercept) 33
2.8 Quality of fitted model 37
2.9 Confidence intervals on mean response and prediction intervals 41
2.10 Simultaneous inference in simple linear regression 47
2.11 A complete annotated computer printout 56
2.12 A look at residuals 57
2.13 Both x and y random 66
Exercises 72
References 80
CHAPTER 3 THE MULTIPLE LINEAR REGRESSION MODEL 82
3.1 Model description and assumptions 82
3.2 The general linear model and the least squares procedure 85
3.3 Properties of least squares estimators under ideal conditions 91
3.4 Hypothesis testing in multiple linear regression 95
3.5 Confidence intervals and prediction intervals in multiple regressions 112
3.6 Data with repeated observations 116
3.7 Simultaneous inference in multiple regression 120
3.8 Multicollinearity in multiple regression data 123
3.9 Quality fit,quality prediction,and the HAT matrix 133
3.10 Categorical or indicator variables(Regression models and ANOVA models) 135
Exercises 153
References 163
CHAPTER 4 CRITERIA FOR CHOICE OF BEST MODEL 164
4.1 Standard criteria for comparing models 165
4.2 Cross validation for model selection and determination of model performance 167
4.3 Conceptual predictive criteria(The Cp=statistic) 178
4.4 Sequential variable selection procedures 185
4.5 Further comments and all possible regressions 193
Exercises 199
References 206
CHAPTER 5 ANALYSIS OF RESIDUALS 209
5.1 Information retrieved from residuals 210
5.2 Plotting of residuals 211
5.3 Studentized residuals 217
5.4 Relation to standardized PRESS residuals 220
5.5 Detection of outliers 221
5.6 Diagnostic plots 231
5.7 Normal residual plots 242
5.8 Further comments on analysis of residuals 244
Exercises 244
References 248
CHAPTER 6 INFLUENCE DIAGNOSTICS 249
6.1 Sources of influence 250
6.2 Diagnostics:Residuals and the HAT matrix 251
6.3 Diagnostics that determine extent of influence 257
6.4 Influence on performance 267
6.5 What do we do with high influence points? 270
Exercises 272
References 273
CHAPTER 7 NONSTANDARD CONDITIONS,VIOLATIONS OF ASSUMPTIONS,AND TRANSFORMATIONS 275
7.1 Heterogeneous variance:Weighted least squares 277
7.2 Problem with correlated errors(Autocorrelation) 287
7.3 Transformations to improve fit and prediction 293
7.4 Regression with a binary response 315
7.5 Further developments in models with a discrete response(Poisson regression) 332
7.6 Generalized linear models 339
7.7 Failure of normality assumption:Presence of outliers 348
7.8 Measurement errors in the regressor variables 357
Exercises 358
References 365
CHAPTER 8 DETECTING AND COMBATING MULTICOLLINEARITY 368
8.1 Multicollinearitv diagnostics 369
8.2 Variance proportions 371
8.3 Further topics concerning multicollinearity 379
8.4 Alternatives to least squares in cases of multicollinea ritv 389
Exercises 419
References 422
CHAPTER 9 NONLINEAR REGRESSION 424
9.1 Nonlinear least squares 425
9.2 Properties of the least squares estimators 425
9.3 The Gauss-Newton procedure for finding estimates 426
9.4 Other modifications of the Gauss-Newton procedure 433
9.5 Some special classes of nonlinear models 436
9.6 Further considerations in nonlinear regression 440
9.7 Why not transform data to 1inearize? 444
Exercises 445
References 449
APPENDIX A SOME SPECIAL CONCEPTS IN MATRIXALGEBRA 452
A.1 Solutions to simultaneous linear equations 452
A.2 Quadratic form 454
A.3 Eigenvalues and eigenvectors 456
A.4 The inverses of a partitioned matrix 458
A.5 Sherman-Morrison-Woodbury theorem 459
References 460
APPENDIX B SOME SPECIAL MANIPULATIONS 461
B.1 Unbiasedness of the residual mean square 461
B.2 Expected value of residual sum of squares and mean square for an underspecified model 462
B.3 The maximum likelihood estimator 464
B.4 Development of the PRESS statistic 465
B.5 Computation of s-i 467
B.6 Dominance of a residual by the corresponding model error 468
B.7 Computation of influence diagnostics 468
B.8 Maximum likelihood estimator in the nonlinear model 470
B.9 Taylor series 470
B.10 Development of the C?-statistic 471
References 473
APPENDIX C STATISTICAL TABLES 474
INDEX 486
- 《经典和现代回归分析及其应用 第2版》(美)麦尔斯(Myers,R.H.)著 2005
- 《应用回归分析》王黎明,陈颖,杨楠编著 2008
- 《应用回归分析》王黎明,张日权,景英川编著 2005
- 《回归分析 北京市高等教育精品教材立项项目》马立平编著 2014
- 《应用回归分析》何晓群,刘义卿编著 2001
- 《回归分析与回归设计:在肥料与栽培试验中的应用》陶勤南编著 1984
- 《应用线性回归分析》周复恭,黄运成编著 1989
- 《应用回归分析》盛承懋等编译 1989
- 《应用回归分析》张小蒂编著 1991
- 《应用回归分析 第2版》何晓群,刘文卿编著 2007
- 《经典和现代回归分析及其应用 第2版》(美)麦尔斯(Myers,R.H.)著 2005
- 《食品安全手册》(美)斯密特(Schmidt,R.H.),(美)罗德瑞克(Rodrick,G.E.)著;石阶平等译 2006
- 《火鸟》(美)米斯蒂·柯普兰著;(美)克里斯托弗·麦尔斯绘;范晓星译 2017
- 《企业、市场与法律》(美)科 斯(Coase,R.H.)著;盛 洪等译 1990
- 《海洋 第3卷》(美)H.U.斯费德鲁普 M.W.约翰逊 R.H.佛莱明著;毛汉礼译 1959
- 《海洋 第2卷》(美)H.U.斯费德鲁普 M.W.约翰逊 R.H.佛莱明著;毛汉礼译 1958
- 《海洋 第1卷》(美)H.U.斯费德鲁普 M.W.约翰逊 R.H.佛莱明著;毛汉礼译 1958
- 《价值分析与价值工程技术 下》(美)L.D麦尔斯著 2222
- 《价值分析与价值工程技术 上》(美)L.D麦尔斯著 2222
- 《语言学简史》R.H.罗宝斯主编 2222
- 《WEB+DB PRESS中文版 2》日本技术评论社编 2015
- 《THE GOVERNMENT/PRESS CONNECTION PRESS OFFICERS AND THEIR OFFICES》STEPHEN HESS 1984
- 《PRESS》POLITICS & PUBLIC OPINION IN BIHAR 1912-1947 2010
- 《Press law》Robin Callender Smith. 1978
- 《SUING THE PRESS》RODNEY A.SMOLLA 1986
- 《THE PRESS AND AMERICA》 2222
- 《FREEDOM OF THE PRESS》ERIC BARENDT 2009
- 《FREEDOM OF THE PRESS》ROB EDELMAN 2006
- 《FREEDOM OF THE PRESS》DAVID L.GEBERT 2005
- 《Racism and the press》Teun A.van Dijk 2016