{"product_id":"quantile-regression-9781119975281","title":"Quantile Regression","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eA guide to the implementation and interpretation of Quantile Regression models    This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface ix\u003c\/p\u003e \u003cp\u003eAcknowledgments xi\u003c\/p\u003e \u003cp\u003eIntroduction xii\u003c\/p\u003e \u003cp\u003eNomenclature xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 A visual introduction to quantile regression 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 1\u003c\/p\u003e \u003cp\u003e1.1 The essential toolkit 1\u003c\/p\u003e \u003cp\u003e1.2 The simplest QR model: The case of the dummy regressor 8\u003c\/p\u003e \u003cp\u003e1.3 A slightly more complex QR model: The case of a nominal regressor 13\u003c\/p\u003e \u003cp\u003e1.4 A typical QR model: The case of a quantitative regressor 15\u003c\/p\u003e \u003cp\u003e1.5 Summary of key points 20\u003c\/p\u003e \u003cp\u003eReferences 21\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Quantile regression: Understanding how and why 22\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 22\u003c\/p\u003e \u003cp\u003e2.1 How and why quantile regression works 22\u003c\/p\u003e \u003cp\u003e2.2 A set of illustrative artificial data 33\u003c\/p\u003e \u003cp\u003e2.3 How and why to work with QR 38\u003c\/p\u003e \u003cp\u003e2.4 Summary of key points 60\u003c\/p\u003e \u003cp\u003eReferences 62\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Estimated coefficients and inference 64\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 64\u003c\/p\u003e \u003cp\u003e3.1 Empirical distribution of the quantile regression estimator 64\u003c\/p\u003e \u003cp\u003e3.2 Inference in QR, the i.i.d. case 76\u003c\/p\u003e \u003cp\u003e3.3 Wald, Lagrange multiplier, and likelihood ratio tests 84\u003c\/p\u003e \u003cp\u003e3.4 Summary of key points 92\u003c\/p\u003e \u003cp\u003eReferences 93\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Additional tools for the interpretation and evaluation of the quantile regression model 94\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 94\u003c\/p\u003e \u003cp\u003e4.1 Data pre-processing 95\u003c\/p\u003e \u003cp\u003e4.2 Response conditional density estimations 107\u003c\/p\u003e \u003cp\u003e4.3 Validation of the model 117\u003c\/p\u003e \u003cp\u003e4.4 Summary of key points 128\u003c\/p\u003e \u003cp\u003eReferences 128\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Models with dependent and with non-identically distributed data 131\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 131\u003c\/p\u003e \u003cp\u003e5.1 A closer look at the scale parameter, the independent and identically distributed case 131\u003c\/p\u003e \u003cp\u003e5.2 The non-identically distributed case 137\u003c\/p\u003e \u003cp\u003e5.3 The dependent data model 152\u003c\/p\u003e \u003cp\u003e5.4 Summary of key points 158\u003c\/p\u003e \u003cp\u003eReferences 158\u003c\/p\u003e \u003cp\u003eAppendix 5.A Heteroskedasticity tests and weighted quantile regression, Stata and R codes 159\u003c\/p\u003e \u003cp\u003e5.A.1 Koenker and Basset test for heteroskedasticity comparing two quantile regressions 159\u003c\/p\u003e \u003cp\u003e5.A.2 Koenker and Basset test for heteroskedasticity comparing all quantile regressions 159\u003c\/p\u003e \u003cp\u003e5.A.3 Quick tests for heteroskedasticity comparing quantile regressions 160\u003c\/p\u003e \u003cp\u003e5.A.4 Compute the individual role of each explanatory variable to the dependent variable 161\u003c\/p\u003e \u003cp\u003e5.A.5 R-codes for the Koenker and Basset test for heteroskedasticity 161\u003c\/p\u003e \u003cp\u003eAppendix 5.B Dependent data 162\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Additional models 163\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 163\u003c\/p\u003e \u003cp\u003e6.1 Nonparametric quantile regression 163\u003c\/p\u003e \u003cp\u003e6.2 Nonlinear quantile regression 172\u003c\/p\u003e \u003cp\u003e6.3 Censored quantile regression 175\u003c\/p\u003e \u003cp\u003e6.4 Quantile regression with longitudinal data 183\u003c\/p\u003e \u003cp\u003e6.5 Group effects through quantile regression 187\u003c\/p\u003e \u003cp\u003e6.6 Binary quantile regression 195\u003c\/p\u003e \u003cp\u003e6.7 Summary of key points 197\u003c\/p\u003e \u003cp\u003eReferences 197\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A Quantile regression and surroundings using R 201\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 201\u003c\/p\u003e \u003cp\u003eA.1 Loading data 202\u003c\/p\u003e \u003cp\u003eA.2 Exploring data 205\u003c\/p\u003e \u003cp\u003eA.3 Modeling data 211\u003c\/p\u003e \u003cp\u003eA.4 Exporting figures and tables 217\u003c\/p\u003e \u003cp\u003eReferences 218\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix B Quantile regression and surroundings using SAS 220\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 220\u003c\/p\u003e \u003cp\u003eB.1 Loading data 221\u003c\/p\u003e \u003cp\u003eB.2 Exploring data 223\u003c\/p\u003e \u003cp\u003eB.3 Modeling data 229\u003c\/p\u003e \u003cp\u003eB.4 Exporting figures and tables 239\u003c\/p\u003e \u003cp\u003eReferences 241\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix C Quantile regression and surroundings using Stata 242\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 242\u003c\/p\u003e \u003cp\u003eC.1 Loading data 243\u003c\/p\u003e \u003cp\u003eC.2 Exploring data 245\u003c\/p\u003e \u003cp\u003eC.3 Modeling data 249\u003c\/p\u003e \u003cp\u003eC.4 Exporting figures and tables 255\u003c\/p\u003e \u003cp\u003eReferences 256\u003c\/p\u003e \u003cp\u003eIndex 257\u003c\/p\u003e","brand":"John Wiley \u0026 Sons 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