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EBookClubs

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Book Nonparametric Estimation of Conditional Quantile Function

Download or read book Nonparametric Estimation of Conditional Quantile Function written by Ashis Kumar Gangopadhyay and published by . This book was released on 1987 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Asymptotic Theory of Nonparametric Estimation of Conditional Quantiles

Download or read book Asymptotic Theory of Nonparametric Estimation of Conditional Quantiles written by Probal Chaudhuri and published by . This book was released on 1988 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonparametric Estimation of Conditional Quantiles

Download or read book Nonparametric Estimation of Conditional Quantiles written by Alexander Kukush and published by . This book was released on 2005 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonparametric Estimation of Conditional Quantile Regression with Mixed Discrete and Continuous Data

Download or read book Nonparametric Estimation of Conditional Quantile Regression with Mixed Discrete and Continuous Data written by Degui Li and published by . This book was released on 2015 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we investigate the nonlinear quantile regression with mixed discrete and continuous regressors. A local linear smoothing technique with the mixed continuous and discrete kernel function is proposed to estimate the conditional quantile regression function. Under some mild conditions, the asymptotic distribution is established for the proposed nonparametric estimators, which can be seen as a generalisation of some existing theory which only handles the case of purely continuous regressors. We further study the choice of the tuning parameters in the local quantile estimation procedure, and suggest using the cross-validation approach to choose the optimal bandwidths. A simulation study is provided to examine the finite sample behavior of the proposed method, which is also compared with the naive local linear quantile estimation without smoothing the discrete regressors and the nonparametric inverse-CDF method proposed by Li, Lin and Racine (2013).

Book A Simple Nonparametric Approach for Estimation and Inference of Conditional Quantile Functions

Download or read book A Simple Nonparametric Approach for Estimation and Inference of Conditional Quantile Functions written by Zheng Fang and published by . This book was released on 2018 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we present a new nonparametric method for estimating a conditional quantile function and develop its weak convergence theory. The proposed estimator is computationally easy-to-implement, and automatically ensures quantile monotonicity by construction. For inference, we propose to use a residual bootstrap method. The Monte Carlo simulations show that our new estimator compares well with the checkfunction-based estimator in terms of estimation mean squared error (MSE), and the bootstrap confidence bands give adequate coverage probabilities. An empirical example considering a dataset from Canadian high school graduate earnings illustrates that the proposed method delivers a more reasonable quantile estimate than the check-function counterpart.

Book Testing Exogeneity

Download or read book Testing Exogeneity written by Neil R. Ericsson and published by . This book was released on 1994 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the nature of exogeneity, a central concept in standard econometrics texts, and shows how to test for it through numerous substantive empirical examples from around the world, including the UK, Argentina, Denmark, Finland, and Norway. Part I defines terms and provides the necessary background; Part II contains applications to models of expenditure, money demand, inflation, wages and prices, and exchange rates; and Part III extends various tests of constancy and forecast accuracy, which are central to testing super exogeneity. About the Series Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.

Book Smooth Nonparametric Conditional Quantile Profit Function Estimation

Download or read book Smooth Nonparametric Conditional Quantile Profit Function Estimation written by Anton Piskunov and published by . This book was released on 2009 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, in an attempt to produce robust production frontier estimators, Aragon et al. [2005, Nonparametric frontier estimation: a conditional quantile-based approach. Econometric Theory 21, 358-389] and Martins-Filho and Yao [2008, A smooth nonparametric conditional quantile frontier estimator. Journal of Econometrics 143, 317-333] considered the estimation of nonparametric [alpha]- frontier models based on conditional quantiles with [alpha][element of] (0,1). There exist, however, a large and growing literature in economics devoted to the estimation of profit functions. In this paper, we first define an [alpha]-profit function based on the quantile of the suitably defined conditional distribution for profits. Second we propose a smooth nonparametric conditional quantile estimator for the [alpha]-profit function model. Our estimator is computationally simple, resistant to outliers and extreme values, and smooth. In addition, the estimator is shown to be consistent and asymptotically normal under mild regularity conditions. A small simulation study provides evidence of the finite sample properties for the estimator.

Book Selected topics on nonparametric conditional quantiles and risk theory

Download or read book Selected topics on nonparametric conditional quantiles and risk theory written by Yebin Cheng and published by Rozenberg Publishers. This book was released on 2007 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Application of a Simple Nonparametric Conditional Quantile Function Estimator in Unemployment Duration Analysis

Download or read book Application of a Simple Nonparametric Conditional Quantile Function Estimator in Unemployment Duration Analysis written by Laura Wichert and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider an extension of conventional univariate Kaplan-Meier type estimators for the hazard rate and the survivor function to multivariate censored data with a censored random regressor. It is an Akritas (1994) type estimator which adapts the nonparametric conditional hazard rate estimator of Beran (1981) to more typical data situations in applied analysis. We show with simulations that the estimator has nice finite sample properties and our implementation appears to be fast. As an application we estimate nonparametric conditional quantile functions with German administrative unemployment duration data.

Book Handbook of Quantile Regression

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.

Book Functional and High Dimensional Statistics and Related Fields

Download or read book Functional and High Dimensional Statistics and Related Fields written by Germán Aneiros and published by Springer. This book was released on 2021-06-21 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing methodological and computational aspects, as well as real-world applications. It covers topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis, and includes applications in automobile engineering, criminology, drawing recognition, economics, environmetrics, medicine, mobile phone data, spectrometrics and urban environments. The book gathers selected, refereed contributions presented at the Fifth International Workshop on Functional and Operatorial Statistics (IWFOS) in Brno, Czech Republic. The workshop was originally to be held on June 24-26, 2020, but had to be postponed as a consequence of the COVID-19 pandemic. Initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008, the IWFOS workshops provide a forum to discuss the latest trends and advances in functional statistics and related fields, and foster the exchange of ideas and international collaboration in the field.

Book Nonparametric Econometrics

Download or read book Nonparametric Econometrics written by Qi Li and published by Princeton University Press. This book was released on 2023-07-18 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, up-to-date textbook on nonparametric methods for students and researchers Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers. Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data—nominal and ordinal—in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory. This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types—continuous, nominal, and ordinal—within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables. Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.

Book Quantile Regression

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.

Book Nonparametric Estimate for Conditional Scale Function from Time Series

Download or read book Nonparametric Estimate for Conditional Scale Function from Time Series written by Peter Nyamuhanga Mwita and published by . This book was released on 2018 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper considers the problem of estimating conditional scale function from time series. We discuss an estimate obtained using kernel version of quantile regression objective function of Keonker and Bassett (1978) and prove its consistency by applying some results, on dependent observations, in White and Wooldridge (1991).

Book Nonparametric Multivariate Conditional Distribution and Quantile Regression

Download or read book Nonparametric Multivariate Conditional Distribution and Quantile Regression written by Keming Yu and published by . This book was released on 2008 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: In nonparametric multivariate regression analysis, one usually seeks methods to reduce the dimensionality of the regression function to bypass the difficulty caused by the curse of dimensionality. We study nonparametric estimation of multivariate conditional distribution and quantile regression via local univariate quadratic estimation of partial derivatives of bivariate copulas. Without restricting the form of underlying regression function or using dimensional reduction, we show that a d-dimensional multivariate conditional distribution and quantile regression could be estimated by d(d 1)/2 times of univariate smoothers. The asymptotic bias and variance as well as smoothing parameter selection method are derived. Simulations show that the method works quite well. The techniques are illustrated by application to exchange rate data.

Book Linear Processes in Function Spaces

Download or read book Linear Processes in Function Spaces written by Denis Bosq and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main subject of this book is the estimation and forecasting of continuous time processes. It leads to a development of the theory of linear processes in function spaces. Mathematical tools are presented, as well as autoregressive processes in Hilbert and Banach spaces and general linear processes and statistical prediction. Implementation and numerical applications are also covered. The book assumes knowledge of classical probability theory and statistics.

Book Nonparametric Econometric Methods and Application

Download or read book Nonparametric Econometric Methods and Application written by Thanasis Stengos and published by MDPI. This book was released on 2019-05-20 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present Special Issue collects a number of new contributions both at the theoretical level and in terms of applications in the areas of nonparametric and semiparametric econometric methods. In particular, this collection of papers that cover areas such as developments in local smoothing techniques, splines, series estimators, and wavelets will add to the existing rich literature on these subjects and enhance our ability to use data to test economic hypotheses in a variety of fields, such as financial economics, microeconomics, macroeconomics, labor economics, and economic growth, to name a few.