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Author: Roger Koenker Publisher: CRC Press ISBN: 1351646567 Category : Mathematics Languages : en Pages : 739
Book Description
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: CRC Press ISBN: 1351646567 Category : Mathematics Languages : en Pages : 739
Book Description
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: Pierre Alquier Publisher: Springer Science & Business Media ISBN: 3642199895 Category : Mathematics Languages : en Pages : 204
Book Description
The “Stats in the Château” summer school was held at the CRC château on the campus of HEC Paris, Jouy-en-Josas, France, from August 31 to September 4, 2009. This event was organized jointly by faculty members of three French academic institutions ─ ENSAE ParisTech, the Ecole Polytechnique ParisTech, and HEC Paris ─ which cooperate through a scientific foundation devoted to the decision sciences. The scientific content of the summer school was conveyed in two courses, one by Laurent Cavalier (Université Aix-Marseille I) on "Ill-posed Inverse Problems", and one by Victor Chernozhukov (Massachusetts Institute of Technology) on "High-dimensional Estimation with Applications to Economics". Ten invited researchers also presented either reviews of the state of the art in the field or of applications, or original research contributions. This volume contains the lecture notes of the two courses. Original research articles and a survey complement these lecture notes. Applications to economics are discussed in various contributions.
Author: Stephen Boyd Publisher: Now Publishers Inc ISBN: 160198460X Category : Computers Languages : en Pages : 138
Book Description
Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.
Author: Econometric Society. World Congress Publisher: Cambridge University Press ISBN: 1107016061 Category : Business & Economics Languages : en Pages : 633
Book Description
The third volume of edited papers from the Tenth World Congress of the Econometric Society 2010.
Author: Daron Acemoglu Publisher: Cambridge University Press ISBN: 1107717825 Category : Business & Economics Languages : en Pages : 633
Book Description
This is the third of three volumes containing edited versions of papers and commentaries presented at invited symposium sessions of the Tenth World Congress of the Econometric Society, held in Shanghai in August 2010. The papers summarize and interpret key developments in economics and econometrics, and they discuss future directions for a wide variety of topics, covering both theory and application. Written by the leading specialists in their fields, these volumes provide a unique, accessible survey of progress on the discipline. The first volume primarily addresses economic theory, with specific focuses on nonstandard markets, contracts, decision theory, communication and organizations, epistemics and calibration, and patents.
Author: Áureo de Paula Publisher: Emerald Group Publishing ISBN: 1838675779 Category : Business & Economics Languages : en Pages : 353
Book Description
Showcasing fresh methodological and empirical research on the econometrics of networks, and comprising both theoretical, empirical and policy papers, the authors in this volume bring together a wide range of perspectives to facilitate a dialogue between academics and practitioners for better understanding this groundbreaking field.
Author: Jean-Gabriel Ganascia Publisher: Springer ISBN: 364233492X Category : Computers Languages : en Pages : 341
Book Description
This book constitutes the refereed proceedings of the 15th International Conference on Discovery Science, DS 2012, held in Lyon, France, in October 2012. The 22 papers presented in this volume were carefully reviewed and selected from 46 submissions. The field of discovery science aims at inducing and validating new scientific hypotheses from data. The scope of this conference includes the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, tools for supporting the human process of discovery in science, as well as their application to knowledge discovery.
Author: Xavier Freixas Publisher: MIT Press ISBN: 0262549018 Category : Business & Economics Languages : en Pages : 487
Book Description
A framework for macroprudential regulation that defines systemic risk and macroprudential policy, describes macroprudential tools, and surveys the effectiveness of existing macroprudential regulation. The recent financial crisis has shattered all standard approaches to banking regulation. Regulators now recognize that banking regulation cannot be simply based on individual financial institutions' risks. Instead, systemic risk and macroprudential regulation have come to the forefront of the new regulatory paradigm. Yet our knowledge of these two core aspects of regulation is still limited and fragmented. This book offers a framework for understanding the reasons for the regulatory shift from a microprudential to a macroprudential approach to financial regulation. It defines systemic risk and macroprudential policy, cutting through the generalized confusion as to their meaning; contrasts macroprudential to microprudential approaches; discusses the interaction of macroprudential policy with macroeconomic policy (monetary policy in particular); and describes macroprudential tools and experiences with macroprudential regulation around the world. The book also considers the remaining challenges for establishing effective macroprudential policy and broader issues in regulatory reform. These include the optimal size and structure of the financial system, the multiplicity of regulatory bodies in the United States, the supervision of cross-border financial institutions, and the need for international cooperation on macroprudential policies.
Author: Jianqing Fan Publisher: CRC Press ISBN: 0429527616 Category : Mathematics Languages : en Pages : 942
Book Description
Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
Author: Jeffrey Racine Publisher: Oxford University Press ISBN: 0199857954 Category : Business & Economics Languages : en Pages : 562
Book Description
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: Roger Koenker
Author: Roger Koenker
Author: Pierre Alquier
Author: Stephen Boyd
Author: Econometric Society. World Congress
Author: Daron Acemoglu
Author: Áureo de Paula
Author: Jean-Gabriel Ganascia
Author: Xavier Freixas
Author: Jianqing Fan
Author: Jeffrey Racine