图书简介
Applied Linear Regression, Fourth Edition has been thoroughly updated to help students master the theory and applications of linear regression modeling. Focusing on model building, assessing fit and reliability, and drawing conclusions, the text demonstrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. To facilitate quick learning, the Fourth Edition stresses the use of graphical methods in an effort to find appropriate models and to better understand them. In that spirit, most analyses and homework problems use graphs for the discovery of structure as well as for the summarization of results. New to this edition are extensive discussions of splines, principal components, lack-of-fit tests, effects plots, invariance of linear regression, R2, misspecification of weights and expansion of the bootstrap and ANOVA. Logistic examples are now integrated throughout the latter half of the book. An eBook version of the printed text, along with test bank and spreadsheet functionalities, is available at wiley.com
馆藏图书馆
Harvard Library
Yale University Library
1 Scatterplots 1 1.1 Scatterplots 2 1.2 Mean Functions 9 1.3 Variance Functions 12 1.4 Summary Graph 12 1.5 Tools for Looking at Scatterplots 13 1.6 Scatterplot Matrices 15 1.7 Problems 17 2 Simple Linear Regression 21 2.1 Ordinary Least Squares Estimation 22 2.2 Least Squares Criterion 24 2.3 Estimating the Variance 2 26 2.4 Properties of Least Squares Estimates 27 2.5 Estimated Variances 28 2.6 Confidence Intervals and -Tests 29 2.7 The Coefficient of Determination, 2 33 2.8 The Residuals 35 2.9 Problems 37 3 Multiple Regression 49 3.1 Adding a Regressor to a Simple Linear Regression Model 49 3.2 The Multiple Linear Regression Model 53 3.3 Predictors and Regressors 53 3.4 Ordinary Least Squares 57 3.5 Predictions, Fitted Values and Linear Combinations 65 3.6 Problems 66 4 Interpretation of Main Effects 71 4.1 Understanding Parameter Estimates 71 4.2 Dropping Regressors 81 4.3 Experimentation Versus Observation 84 4.4 Sampling from a Normal Population 86 4.5 More on 2 88 4.6 Problems 90 5 Complex Regressors 95 5.1 Factors 95 5.2 Many Factors 105 5.3 Polynomial Regression 106 5.4 Splines 109 5.5 Principal Components 112 5.6 Missing Data 115 5.7 Problems 118 6 Testing and Analysis of Variance 129 6.1 -tests 130 6.2 The Analysis of Variance 134 6.3 Comparisons of Means 138 6.4 Power and Non-null Distributions 138 6.5 Wald Tests 140 6.6 Interpreting Tests 142 6.7 Problems 145 7 Variances 151 7.1 Weighted Least Squares 151 7.2 Misspecified Variances 157 7.3 General Correlation Structures 162 7.4 Mixed Models 163 7.5 Variance Stabilizing Transformations 165 7.6 The Delta Method 166 7.7 The Bootstrap 168 7.8 Problems 173 8 Transformations 179 8.1 Transformation Basics 179 8.2 A General Approach to Transformations 185 8.3 Transforming the Response 190 8.4 Transformations of Nonpositive Variables 192 8.5 Additive Models 192 8.6 Problems 193 9 Regression Diagnostics 199 9.1 The Residuals 199 9.2 Testing for Curvature 206 9.3 Nonconstant Variance 208 9.4 Outliers 208 9.5 Influence of Cases 212 9.6 Normality Assumption 218 9.7 Problems 220 10 Variable Selection 227 10.1 Variable Selection and Parameter Assessment 228 10.2 Variable Selection for Discovery 230 10.3 Model Selection for Prediction 238 10.4 Problems 241 11 Nonlinear Regression 245 11.1 Estimation for Nonlinear Mean Functions 246 11.2 Inference Assuming Large Samples 249 11.3 Starting Values 249 11.4 Bootstrap Inference 255 11.5 Further Reading 257 11.6 Problems 258 12 Binomial and Poisson Regression 263 12.1 Distributions for Counted Data 263 12.2 Regression Models For Counts 265 12.3 Poisson Regression 271 12.4 Transferring What You Know about Linear Models 276 12.5 Generalized Linear Models 278 12.6 Problems 278 A Appendix 283 A.1 Website 283 A.2 Means, Variances, Covariances and Correlations 283 A.3 Least Squares for Simple Regression 286 A.4 Means and Variances of Least Squares Estimates 286 A.5 Estimating E( |) using a Smoother 288 A.6 A Brief Introduction to Matrices and Vectors 290 A.7 Random Vectors 295 A.8 Least Squares Using Matrices 295 A.9 The QR factorization 299 A.10 Spectral Decomposition 300 A.11 Maximum Likelihood Estimates 300 A.12 The Box-Cox Method for Transformations 302 A.13 Case Deletion in Linear Regression 305 Bibliography 321 Index 322
Trade Policy 买家须知
- 关于产品:
- ● 正版保障:本网站隶属于中国国际图书贸易集团公司,确保所有图书都是100%正版。
- ● 环保纸张:进口图书大多使用的都是环保轻型张,颜色偏黄,重量比较轻。
- ● 毛边版:即书翻页的地方,故意做成了参差不齐的样子,一般为精装版,更具收藏价值。
关于退换货:
- 由于预订产品的特殊性,采购订单正式发订后,买方不得无故取消全部或部分产品的订购。
- 由于进口图书的特殊性,发生以下情况的,请直接拒收货物,由快递返回:
- ● 外包装破损/发错货/少发货/图书外观破损/图书配件不全(例如:光盘等)
并请在工作日通过电话400-008-1110联系我们。
- 签收后,如发生以下情况,请在签收后的5个工作日内联系客服办理退换货:
- ● 缺页/错页/错印/脱线
关于发货时间:
- 一般情况下:
- ●【现货】 下单后48小时内由北京(库房)发出快递。
- ●【预订】【预售】下单后国外发货,到货时间预计5-8周左右,店铺默认中通快递,如需顺丰快递邮费到付。
- ● 需要开具发票的客户,发货时间可能在上述基础上再延后1-2个工作日(紧急发票需求,请联系010-68433105/3213);
- ● 如遇其他特殊原因,对发货时间有影响的,我们会第一时间在网站公告,敬请留意。
关于到货时间:
- 由于进口图书入境入库后,都是委托第三方快递发货,所以我们只能保证在规定时间内发出,但无法为您保证确切的到货时间。
- ● 主要城市一般2-4天
- ● 偏远地区一般4-7天
关于接听咨询电话的时间:
- 010-68433105/3213正常接听咨询电话的时间为:周一至周五上午8:30~下午5:00,周六、日及法定节假日休息,将无法接听来电,敬请谅解。
- 其它时间您也可以通过邮件联系我们:customer@readgo.cn,工作日会优先处理。
关于快递:
- ● 已付款订单:主要由中通、宅急送负责派送,订单进度查询请拨打010-68433105/3213。
本书暂无推荐
本书暂无推荐