Quantile Regression: Estimation and Simulation, Volume 2 - Rilegato

Furno, Marilena; Vistocco, Domenico

 
9781118863596: Quantile Regression: Estimation and Simulation, Volume 2
Rilegato
ISBN 10: 1118863593 ISBN 13: 9781118863596
Casa editrice: Wiley, 2018

Sinossi

Contains an overview of several technical topics of Quantile Regression

Volume two of Quantile Regression offers an important guide for applied researchers that draws on the same example-based approach adopted for the first volume. The text explores topics including robustness, expectiles, m-quantile, decomposition, time series, elemental sets and linear programming. Graphical representations are widely used to visually introduce several issues, and to illustrate each method. All the topics are treated theoretically and using real data examples. Designed as a practical resource, the book is thorough without getting too technical about the statistical background.

The authors cover a wide range of QR models useful in several fields. The software commands in R and Stata are available in the appendixes and featured on the accompanying website. The text:

  • Provides an overview of several technical topics such as robustness of quantile regressions, bootstrap and elemental sets, treatment effect estimators
  • Compares quantile regression with alternative estimators like expectiles, M-estimators and M-quantiles
  • Offers a general introduction to linear programming focusing on the simplex method as solving method for the quantile regression problem
  • Considers time-series issues like non-stationarity, spurious regressions, cointegration, conditional heteroskedasticity via quantile regression
  • Offers an analysis that is both theoretically and practical
  • Presents real data examples and graphical representations to explain the technical issues

Written for researchers and students in the fields of statistics, economics, econometrics, social and environmental science, this text offers guide to the theory and application of quantile regression models.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull'autore

Marilena Furno, Department of Agriculture, University of Naples Federico II, Italy

Domenico Vistocco, Department of Economics and Law, University of Cassino, Italy

Dalla quarta di copertina

Contains an Overview of Several Technical Topics of Quantile Regression

Volume Two of Quantile Regression offers an important guide for applied researchers that draws on the same example-based approach adopted for the first volume. The text explores topics including robustness, expectiles, M-quantile, decomposition, time series, elemental sets and linear programming. Graphical representations are widely used to visually introduce several issues, and to illustrate each method. All the topics are treated theoretically and using real data examples. Designed as a practical resource, the book is thorough without getting too technical about the statistical background.

The authors cover a wide range of QR models useful in several fields. The software commands in R and Stata are available in the appendixes and featured on the accompanying website. The text:

  • Provides an overview of several technical topics such as robustness of quantile regressions, bootstrap and elemental sets and treatments effect estimators
  • Compares quantile regression with alternative estimators like expectiles, M-estimators and M-quantiles
  • Offers a general introduction to linear programming focusing on the simplex method as solving method for the quantile regression problem
  • Considers time-series issues like non-stationarity, spurious regressions, cointegration, and conditional heteroskedasticity via quantile regression
  • Offers an analysis that is both theoretical and practical
  • Presents real data examples and graphical representations to explain the technical issues

Written for researchers and students in the fields of statistics, economics, econometrics, social and environmental science, this text offers guide to the theory and application of quantile regression models.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Wiley
Data di pubblicazione
2018
Lingua
Inglese
ISBN 10 
1118863593
ISBN 13 
9781118863596
Rilegatura
Copertina rigida
Numero di pagine
307
Contatto del produttore
non disponibile
Persona responsabile
non disponibile