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Author : Xuming He
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (115 download)
Download or read book Quantile Regression Estimates for a Class of Linear and Partially Linear Errors-in-Variables Models written by Xuming He and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Marilena Furno
Publisher : John Wiley & Sons
ISBN 13 : 111886364X
Total Pages : 311 pages
Book Rating : 4.1/5 (188 download)
Download or read book Quantile Regression written by Marilena Furno and published by John Wiley & Sons. This book was released on 2018-07-18 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Roger Koenker
Publisher : CRC Press
ISBN 13 : 1351646567
Total Pages : 739 pages
Book Rating : 4.3/5 (516 download)
Download or read book Handbook of Quantile Regression written by Roger Koenker and published by CRC Press. This book was released on 2017-10-12 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions. Median regression, as introduced in the 18th century by Boscovich and Laplace, is a special case. In contrast to conventional mean regression that minimizes sums of squared residuals, median regression minimizes sums of absolute residuals; quantile regression simply replaces symmetric absolute loss by asymmetric linear loss. Since its introduction in the 1970's by Koenker and Bassett, quantile regression has been gradually extended to a wide variety of data analytic settings including time series, survival analysis, and longitudinal data. By focusing attention on local slices of the conditional distribution of response variables it is capable of providing a more complete, more nuanced view of heterogeneous covariate effects. Applications of quantile regression can now be found throughout the sciences, including astrophysics, chemistry, ecology, economics, finance, genomics, medicine, and meteorology. Software for quantile regression is now widely available in all the major statistical computing environments. The objective of this volume is to provide a comprehensive review of recent developments of quantile regression methodology illustrating its applicability in a wide range of scientific settings. The intended audience of the volume is researchers and graduate students across a diverse set of disciplines.
Author : Roger Koenker
Publisher : Cambridge University Press
ISBN 13 : 1139444719
Total Pages : 367 pages
Book Rating : 4.1/5 (394 download)
Download or read book Quantile Regression written by Roger Koenker and published by Cambridge University Press. This book was released on 2005-05-05 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. By complementing the exclusive focus of classical least squares regression on the conditional mean, quantile regression offers a systematic strategy for examining how covariates influence the location, scale and shape of the entire response distribution. This monograph is the first comprehensive treatment of the subject, encompassing models that are linear and nonlinear, parametric and nonparametric. The author has devoted more than 25 years of research to this topic. The methods in the analysis are illustrated with a variety of applications from economics, biology, ecology and finance. The treatment will find its core audiences in econometrics, statistics, and applied mathematics in addition to the disciplines cited above.
Author : Lingxin Hao
Publisher : SAGE Publications
ISBN 13 : 1483316904
Total Pages : 142 pages
Book Rating : 4.4/5 (833 download)
Download or read book Quantile Regression written by Lingxin Hao and published by SAGE Publications. This book was released on 2007-04-18 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantile Regression, the first book of Hao and Naiman′s two-book series, establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literature exists for each subject, the authors seek to explore the natural connections between this increasingly sought-after tool and research topics in the social sciences. Quantile regression as a method does not rely on assumptions as restrictive as those for the classical linear regression; though more traditional models such as least squares linear regression are more widely utilized, Hao and Naiman show, in their application of quantile regression to empirical research, how this model yields a more complete understanding of inequality. Inequality is a perennial concern in the social sciences, and recently there has been much research in health inequality as well. Major software packages have also gradually implemented quantile regression. Quantile Regression will be of interest not only to the traditional social science market but other markets such as the health and public health related disciplines. Key Features: Establishes a natural link between quantile regression and inequality studies in the social sciences Contains clearly defined terms, simplified empirical equations, illustrative graphs, empirical tables and graphs from examples Includes computational codes using statistical software popular among social scientists Oriented to empirical research
Author : Jorge M. Uribe
Publisher : Springer Nature
ISBN 13 : 3030445046
Total Pages : 63 pages
Book Rating : 4.0/5 (34 download)
Download or read book Quantile Regression for Cross-Sectional and Time Series Data written by Jorge M. Uribe and published by Springer Nature. This book was released on 2020-03-30 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: This brief addresses the estimation of quantile regression models from a practical perspective, which will support researchers who need to use conditional quantile regression to measure economic relationships among a set of variables. It will also benefit students using the methodology for the first time, and practitioners at private or public organizations who are interested in modeling different fragments of the conditional distribution of a given variable. The book pursues a practical approach with reference to energy markets, helping readers learn the main features of the technique more quickly. Emphasis is placed on the implementation details and the correct interpretation of the quantile regression coefficients rather than on the technicalities of the method, unlike the approach used in the majority of the literature. All applications are illustrated with R.
Author : Roger Koenker
Publisher : CRC Press
ISBN 13 : 1498725295
Total Pages : 463 pages
Book Rating : 4.4/5 (987 download)
Download or read book Handbook of Quantile Regression written by Roger Koenker and published by CRC Press. This book was released on 2017-10-12 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions. Median regression, as introduced in the 18th century by Boscovich and Laplace, is a special case. In contrast to conventional mean regression that minimizes sums of squared residuals, median regression minimizes sums of absolute residuals; quantile regression simply replaces symmetric absolute loss by asymmetric linear loss. Since its introduction in the 1970's by Koenker and Bassett, quantile regression has been gradually extended to a wide variety of data analytic settings including time series, survival analysis, and longitudinal data. By focusing attention on local slices of the conditional distribution of response variables it is capable of providing a more complete, more nuanced view of heterogeneous covariate effects. Applications of quantile regression can now be found throughout the sciences, including astrophysics, chemistry, ecology, economics, finance, genomics, medicine, and meteorology. Software for quantile regression is now widely available in all the major statistical computing environments. The objective of this volume is to provide a comprehensive review of recent developments of quantile regression methodology illustrating its applicability in a wide range of scientific settings. The intended audience of the volume is researchers and graduate students across a diverse set of disciplines.
Author : Wolfgang Härdle
Publisher : Springer Science & Business Media
ISBN 13 : 3642577008
Total Pages : 210 pages
Book Rating : 4.6/5 (425 download)
Download or read book Partially Linear Models written by Wolfgang Härdle and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics. Many methods and techniques have been proposed and studied. This monograph hopes to bring an up-to-date presentation of the state of the art of partially linear regression techniques. The emphasis is on methodologies rather than on the theory, with a particular focus on applications of partially linear regression techniques to various statistical problems. These problems include least squares regression, asymptotically efficient estimation, bootstrap resampling, censored data analysis, linear measurement error models, nonlinear measurement models, nonlinear and nonparametric time series models.
Author : Cristina Davino
Publisher : John Wiley & Sons
ISBN 13 : 111997528X
Total Pages : 288 pages
Book Rating : 4.1/5 (199 download)
Download or read book Quantile Regression written by Cristina Davino and published by John Wiley & Sons. This book was released on 2013-12-31 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: A 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. The main focus of this book is to provide the reader with a comprehensive description of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and followed by applications using real data. Quantile Regression: Presents a complete treatment of quantile regression methods, including, estimation, inference issues and application of methods. Delivers a balance between methodolgy and application Offers an overview of the recent developments in the quantile regression framework and why to use quantile regression in a variety of areas such as economics, finance and computing. Features a supporting website (www.wiley.com/go/quantile_regression) hosting datasets along with R, Stata and SAS software code. Researchers and PhD students in the field of statistics, economics, econometrics, social and environmental science and chemistry will benefit from this book.
Author : Grace Y. Yi
Publisher : Springer
ISBN 13 : 1493966405
Total Pages : 497 pages
Book Rating : 4.4/5 (939 download)
Download or read book Statistical Analysis with Measurement Error or Misclassification written by Grace Y. Yi and published by Springer. This book was released on 2017-08-02 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems. Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methods—such as likelihood and estimating function theory—or modeling schemes in varying settings—such as survival analysis and longitudinal data analysis—can result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material. The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods. This text can serve as a reference book for researchers interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data. Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute.
Author : Cristina Davino
Publisher : John Wiley & Sons
ISBN 13 : 1118752716
Total Pages : 288 pages
Book Rating : 4.1/5 (187 download)
Download or read book Quantile Regression written by Cristina Davino and published by John Wiley & Sons. This book was released on 2013-10-24 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: A 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. The main focus of this book is to provide the reader with a comprehensive description of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and followed by applications using real data. Quantile Regression: Presents a complete treatment of quantile regression methods, including, estimation, inference issues and application of methods. Delivers a balance between methodolgy and application Offers an overview of the recent developments in the quantile regression framework and why to use quantile regression in a variety of areas such as economics, finance and computing. Features a supporting website (www.wiley.com/go/quantile_regression) hosting datasets along with R, Stata and SAS software code. Researchers and PhD students in the field of statistics, economics, econometrics, social and environmental science and chemistry will benefit from this book.
Author : Yiguo Sun
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (593 download)
Download or read book Square Root N - Consistent Semiparametric Estimation of Partially Linear Quantile Regression Models written by Yiguo Sun and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jerry A. Hausman
Publisher :
ISBN 13 :
Total Pages : 67 pages
Book Rating : 4.:/5 (11 download)
Download or read book Errors in the Dependent Variable of Quantile Regression Models written by Jerry A. Hausman and published by . This book was released on 2019 with total page 67 pages. Available in PDF, EPUB and Kindle. Book excerpt: The popular quantile regression estimator of Koenker and Bassett (1978) is biased if there is an additive error term. Approaching this problem as an errors-in-variables problem where the dependent variable suffers from classical measurement error, we present a sieve maximum-likelihood approach that is robust to left-hand side measurement error. After providing sufficient conditions for identification, we demonstrate that when the number of knots in the quantile grid is chosen to grow at an adequate speed, the sieve maximum-likelihood estimator is consistent and asymptotically normal, permitting inference via bootstrapping. We verify our theoretical results with Monte Carlo simulations and illustrate our estimator with an application to the returns to education highlighting changes over time in the returns to education that have previously been masked by measurement-error bias.
Author : Leandro Pardo
Publisher : MDPI
ISBN 13 : 3038979368
Total Pages : 344 pages
Book Rating : 4.0/5 (389 download)
Download or read book New Developments in Statistical Information Theory Based on Entropy and Divergence Measures written by Leandro Pardo and published by MDPI. This book was released on 2019-05-20 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents new and original research in Statistical Information Theory, based on minimum divergence estimators and test statistics, from a theoretical and applied point of view, for different statistical problems with special emphasis on efficiency and robustness. Divergence statistics, based on maximum likelihood estimators, as well as Wald’s statistics, likelihood ratio statistics and Rao’s score statistics, share several optimum asymptotic properties, but are highly non-robust in cases of model misspecification under the presence of outlying observations. It is well-known that a small deviation from the underlying assumptions on the model can have drastic effect on the performance of these classical tests. Specifically, this book presents a robust version of the classical Wald statistical test, for testing simple and composite null hypotheses for general parametric models, based on minimum divergence estimators.
Author : Jeffrey Racine
Publisher : Oxford University Press
ISBN 13 : 0199857954
Total Pages : 562 pages
Book Rating : 4.1/5 (998 download)
Download or read book The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics written by Jeffrey Racine and published by Oxford University Press. This book was released on 2013-12-31 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. These data-driven models seek to replace the classical parametric models of the past, which were rigid and often linear. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures. They provide a balanced view of new developments in the modeling of cross-section, time series, panel, and spatial data. Topics of the volume include: the methodology of semiparametric models and special regressor methods; inverse, ill-posed, and well-posed problems; methodologies related to additive models; sieve regression, nonparametric and semiparametric regression, and the true error of competing approximate models; support vector machines and their modeling of default probability; series estimation of stochastic processes and their application in Econometrics; identification, estimation, and specification problems in semilinear time series models; nonparametric and semiparametric techniques applied to nonstationary or near nonstationary variables; the estimation of a set of regression equations; and a new approach to the analysis of nonparametric models with exogenous treatment assignment.
Author : Kaddour Hadri
Publisher : World Scientific
ISBN 13 : 9814513474
Total Pages : 616 pages
Book Rating : 4.8/5 (145 download)
Download or read book Econometric Methods and Their Applications in Finance, Macro and Related Fields written by Kaddour Hadri and published by World Scientific. This book was released on 2014 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume aims at providing an outlet for some of the best papers presented at the 15th Annual Conference of the African Econometric Society, which is one of the OC chaptersOCO of the International Econometric Society. Many of these papers represent the state of the art in financial econometrics and applied econometric modeling, and some also provide useful simulations that shed light on the models'' ability to generate meaningful scenarios for forecasting and policy analysis. Contents: Financial Econometrics and International Finance: Modeling Interest Rates Using Reducible Stochastic Differential Equations: A Copula-Based Multivariate Approach (Ruijun Bu, Ludovic Giet, Kaddour Hadri and Michel Lubrano); Financial Risk Management Using Asymmetric Heavy-Tailed Distribution and Nonlinear Dependence Structures of Asset Returns Under Discontinuous Dynamics (Alaa El-Shazly); Modeling Time-Varying Dependence in the Term Structure of Interest Rates (Diaa Noureldin); Nonlinear Filtering and Market Implied Rating for a Jump-Diffusion Structural Model of Credit Risk (Alaa El-Shazly); Time-Varying Optimal Weights for International Asset Allocation in African and South Asian Markets (Dalia El-Edel); Econometric Theory and Methods: Econometric Methods for Ordered Responses: Some Recent Developments (Franco Peracchi); Which Quantile Is the Most Informative? Maximum Likelihood, Maximum Entropy and Quantile Regression (Anil K Bera, Antonio F Galvao Jr., Gabriel V Montes-Rojas, Sung Y Park); The Experimetrics of Fairness (Anna Conte and Peter Moffatt); Uniform in Bandwidth Tests of Specification for Conditional Moment Restrictions Models (Pascal Lavergne and Pierre Nguimkeu); Joint LM Test for Homoscedasticity in a Two Way Error Components Model (Eugene Kouassi, Joel Sango, J M BossonBrou and Kern O Kymn); An Approximation to the Distribution of the Pooled Estimator When the Time Series Equation Is One of a Complete System (Ghazal Amer and William Mikhail); Monetary, Labor, Environmental and Other Econometric Applications: Monetary Policy and the Role of the Exchange Rate in Egypt (Tarek Morsi and Mai El-Mossallamy); International Migration, Remittances and Household Poverty Status in Egypt (Rania Roushdy, Ragui Assaad and Ali Rashed); Determinants of Job Quality and Wages of the Working Poor: Evidence From 1998OCo2006 Egypt Labor Market Panel Survey (Mona Said); A Contract-Theoretic Model of Conservation Agreements (Heidi Gjertsen, Theodore Groves, David A Miller, Eduard Niesten, Dale Squires and Joel Watson); Household Environment and Child Health in Egypt (Mahmoud Hailat and Franco Peracchi); Modeling the Relationship between Natural Resource Abundance, Economic Growth, and the Environment: A Cross-Country Study (Hala Abou-Ali and Yasmine M Abdelfattah); Global Cement Industry: Competitive and Institutional Frameworks (Tarek H Selim and Ahmed S Salem); On the Occurrence of Ponzi Schemes in Presence of Credit Restrictions Penalizing Default (Abdelkrim Seghir); Is Targeted Advertising Always Beneficial? (Nada Ben Elhadj-Ben Brahim, Rim Lahmandi-Ayed and Didier Laussel). Readership: Graduate students and researchers in the fields of econometrics, economic theory, applied econometrics.
Author : Jana Jurečková
Publisher : CRC Press
ISBN 13 : 1351975137
Total Pages : 254 pages
Book Rating : 4.3/5 (519 download)
Download or read book Robust Statistical Methods with R, Second Edition written by Jana Jurečková and published by CRC Press. This book was released on 2019-05-29 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new developments and on the computational aspects. There are many numerical examples and notes on the R environment, and the updated chapter on the multivariate model contains additional material on visualization of multivariate data in R. A new chapter on robust procedures in measurement error models concentrates mainly on the rank procedures, less sensitive to errors than other procedures. This book will be an invaluable resource for researchers and postgraduate students in statistics and mathematics. Features • Provides a systematic, practical treatment of robust statistical methods • Offers a rigorous treatment of the whole range of robust methods, including the sequential versions of estimators, their moment convergence, and compares their asymptotic and finite-sample behavior • The extended account of multivariate models includes the admissibility, shrinkage effects and unbiasedness of two-sample tests • Illustrates the small sensitivity of the rank procedures in the measurement error model • Emphasizes the computational aspects, supplies many examples and illustrations, and provides the own procedures of the authors in the R software on the book’s website
