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Quantile Regression

Author: Lingxin Hao
Publisher: SAGE
ISBN: 9781412926287
Size: 58.11 MB
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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

Quantile Regression

Author: Cristina Davino
Publisher: John Wiley & Sons
ISBN: 111997528X
Size: 37.28 MB
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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.

Quantile Regression

Author: Roger Koenker
Publisher: Cambridge University Press
ISBN: 1139444719
Size: 26.85 MB
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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.

Quantile Regression For Spatial Data

Author: Daniel P. McMillen
Publisher: Springer Science & Business Media
ISBN: 3642318150
Size: 38.48 MB
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Quantile regression analysis differs from more conventional regression models in its emphasis on distributions. Whereas standard regression procedures show how the expected value of the dependent variable responds to a change in an explanatory variable, quantile regressions imply predicted changes for the entire distribution of the dependent variable. Despite its advantages, quantile regression is still not commonly used in the analysis of spatial data. The objective of this book is to make quantile regression procedures more accessible for researchers working with spatial data sets. The emphasis is on interpretation of quantile regression results. A series of examples using both simulated and actual data sets shows how readily seemingly complex quantile regression results can be interpreted with sets of well-constructed graphs. Both parametric and nonparametric versions of spatial models are considered in detail.

Handbook Of Quantile Regression

Author: Roger Koenker
Publisher: CRC Press
ISBN: 1351646567
Size: 44.61 MB
Format: PDF, Kindle
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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.

Statistical Graphics For Univariate And Bivariate Data

Author: William G. Jacoby
Publisher: SAGE Publications
ISBN: 1452215049
Size: 26.66 MB
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Graphical displays that researchers can employ as an integral part of the data analysis process are frequently more revealing than traditional, numerical summary statistics. Providing strategies for examining data more effectively, this volume focuses on: univariate methods such as histograms, smoothed histograms, univariate scatterplots, quantile plots, box plots, dot plots. It describes bivariate methods such as scatterplot construction guidelines, jittering for overplotted points, marginal boxplots, scatterplot slicing, the Loess procedure for nonparametric scatterplot smoothing, and banking to 45 degrees for enhanced visual perception.

Statistics For Geography And Environmental Science

Author: Richard Harris
Publisher: Routledge
ISBN: 1317904400
Size: 39.28 MB
Format: PDF
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Statistics are important tools for validating theory, making predictions and engaging in policy research. They help to provide informed commentary about social and environmental issues, and to make the case for change. Knowledge of statistics is therefore a necessary skill for any student of geography or environmental science. This textbook is aimed at students on a degree course taking a module in statistics for the first time. It focuses on analysing, exploring and making sense of data in areas of core interest to physical and human geographers, and to environmental scientists. It covers the subject in a broadly conventional way from descriptive statistics, through inferential statistics to relational statistics but does so with an emphasis on applied data analysis throughout.

Microeconometrics

Author: A. Colin Cameron
Publisher: Cambridge University Press
ISBN: 1139444867
Size: 40.12 MB
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This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on seven large and exceptionally rich data sets.

Liquidity Risk Efficiency And New Bank Business Models

Author: Santiago Carbó Valverde
Publisher: Springer
ISBN: 331930819X
Size: 74.19 MB
Format: PDF, ePub, Docs
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This book provides insight into current research topics in finance and banking in the aftermath of the financial crisis. In this volume, authors present empirical research on liquidity risk discussed in the context of Basel III and its implications. Chapters also investigate topics such as bank efficiency and new bank business models from a business diversification perspective, the effects on financial exclusion and how liquidity mismatches are related with the bank business model. This book will be of value to those with an interest in how Basel III has had a tangible impact upon banking processes, particularly with regard to maintaining liquidity, and the latest research in financial business models.

Ict Diffusion In Developing Countries

Author: Ewa Lechman
Publisher: Springer
ISBN: 3319182544
Size: 17.58 MB
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This book provides an extensive overview of the diffusion of Information and Communication Technologies (ICTs) in developing countries between 2000 and 2012. It covers issues such as country-specific ICT diffusion patterns, technological substitution and technological convergence. By identifying social, economic and institutional prerequisites and analyzing critical country-specific conditions, the author develops a new approach to explaining the emergence of their technological takeoff. Readers will discover how developing countries are now adopting ICTs, rapidly catching up with the developed world in terms of ICT access and use.