Quantile regression : theory and applications / Cristina Davino, Marilena Furno, Domenico Vistocco

By:

Davino, Cristina [VerfasserIn]

Contributor(s):

Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Wiley series in probability and statisticsPublisher: New York : John Wiley & Sons, Incorporated, [2014]Copyright date: © 2014Description: 1 Online Ressource (XVI, 260 Seiten)ISBN:

9781306069267
9781118753194

Subject(s):

Additional physical formats: 9781119975281 | Erscheint auch als: Quantile regression. Druck-Ausgabe 1. publ. Chichester : Wiley, 2014. XVI, 260 SMSC: MSC: *62-02 | 62G08 | 62Pxx | 62-01RVK: RVK: SK 840LOC classification:

QA278.2

Online resources:

Zugang im Netz des KIT

Summary: Intro -- Quantile Regression: Theory and Applications -- Copyright -- Contents -- Preface -- Acknowledgments -- Introduction -- Nomenclature -- 1 A visual introduction to quantile regression -- Introduction -- 1.1 The essential toolkit -- 1.1.1 Unconditional mean, unconditional quantiles and surroundings -- 1.1.2 Technical insight: Quantiles as solutions of a minimization problem -- 1.1.3 Conditional mean, conditional quantiles and surroundings -- 1.2 The simplest QR model: The case of the dummy regressor -- 1.3 A slightly more complex QR model: The case of a nominal regressor -- 1.4 A typical QR model: The case of a quantitative regressor -- 1.5 Summary of key points -- References -- 2 Quantile regression: Understanding how and why -- Introduction -- 2.1 How and why quantile regression works -- 2.1.1 The general linear programming problem -- 2.1.2 The linear programming formulation for the QR problem -- 2.1.3 Methods for solving the linear programming problem -- 2.2 A set of illustrative artificial data -- 2.2.1 Homogeneous error models -- 2.2.2 Heterogeneous error models -- 2.2.3 Dependent data error models -- 2.3 How and why to work with QR -- 2.3.1 QR for homogeneous and heterogeneous models -- 2.3.2 QR prediction intervals -- 2.3.3 A note on the quantile process -- 2.4 Summary of key points -- References -- 3 Estimated coefficients and inference -- Introduction -- 3.1 Empirical distribution of the quantile regression estimator -- 3.1.1 The case of i.i.d. errors -- 3.1.2 The case of i.ni.d. errors -- 3.1.3 The case of dependent errors -- 3.2 Inference in QR, the i.i.d. case -- 3.3 Wald, Lagrange multiplier, and likelihood ratio tests -- 3.4 Summary of key points -- References -- 4 Additional tools for the interpretation and evaluation of the quantile regression model -- Introduction -- 4.1 Data pre-processing.PPN: PPN: 1657675394Package identifier: Produktsigel: ZDB-26-MYL | BSZ-30-PQE-K1DLR | ZDB-30-PQE | ZDB-30-PAD

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