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Author : Yazhen Wang
Publisher :
ISBN 13 :
Total Pages : 302 pages
Book Rating : 4.:/5 (33 download)
Download or read book Nonparametric Estimation Subject to Shape Restrictions written by Yazhen Wang and published by . This book was released on 1992 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Piet Groeneboom
Publisher : Cambridge University Press
ISBN 13 : 0521864011
Total Pages : 429 pages
Book Rating : 4.5/5 (218 download)
Download or read book Nonparametric Estimation under Shape Constraints written by Piet Groeneboom and published by Cambridge University Press. This book was released on 2014-12-11 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces basic concepts of shape constrained inference and guides the reader to current developments in the subject.
Author : Shabnam Fani
Publisher :
ISBN 13 :
Total Pages : 126 pages
Book Rating : 4.:/5 (915 download)
Download or read book Nonparametric Survival Analysis Under Shape Restrictions written by Shabnam Fani and published by . This book was released on 2014 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main problem studied in this thesis is to analyse and model time-to- event data, particularly when the survival times of subjects under study are not exactly observed. One of the primary tasks in the analysis of survival data is to study the distribution of the event times of interest. In order to avoid strict assumptions associated with a parametric model, we resort to nonparametric methods for estimating a function. Although other nonparametric approaches, such as Kaplan-Meier, kernel-based, and roughness penalty methods, are popular tools for solving function estimation problems, they suffer from some non-trivial issues like the loss of some important information about the true underlying function, difficulties with bandwidth or tuning parameter selection. In contrast, one can avoid these issues at the cost of enforcing some qualitative shape constraints on the function to be estimated. We confine our survival analysis studies to estimating a hazard function since it may make a lot of practical sense to impose certain shape constraints on it. Specifically, we study the problem of nonparametric estimation of a hazard function subject to convex shape restrictions, which naturally entails monotonicity constraints. In this thesis, three main objectives are addressed. Firstly, the problem of nonparametric maximum-likelihood estimation of a hazard function under convex shape restrictions is investigated. We introduce a new nonparametric approach to estimating a convex hazard function in the case of exact observations, the case of interval-censored observations, and the mixed case of exact and interval-censored observations. A new idea to handle the problem of choosing the minimum of a convex hazard function estimate is proposed. Based on this, a new fast algorithm for nonparametric hazard function estimation under convexity shape constraints is developed. Theoretical justification for the convergence of the new algorithm is provided. Secondly, nonparametric estimation of a hazard function under smoothness and convex shape assumptions is studied. Particularly, our nonparametric maximum-likelihood approach is generalized for smooth estimation of a function by applying a higher-order smoothness assumption of an estimator. We also evaluate the performance of the estimators using simulation studies and real-world data. Numerical studies suggest that the shape-constrained estimators generally outperform their unconstrained competitors. Moreover, the empirical results indicate that the smooth shape-restricted estimator has more capability to model human mortality data compared to the piecewise linear continuous estimator, specifically in the infant mortality phase. Lastly, our nonparametric estimation of a hazard function approach under convex shape restrictions is extended to the Cox proportional hazards model. A new algorithm is also developed to estimate both convex baseline hazard function and the effects of covariates on survival times. Numerical studies reveal that our new approaches generally dominate the traditional partial likelihood method in the case of right-censored data and the fully semiparametric maximum likelihood estimation method in the case of interval-censored data. Overall, our series of studies show that the shape-restricted approach tends to provide more accurate estimation than its unconstrained competitors, and further investigations in this direction can be highly fruitful.
Author : Joel Horowitz
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (956 download)
Download or read book Nonparametric Estimation and Inference Under Shape Restrictions written by Joel Horowitz and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic theory often provides shape restrictions on functions of interest in applications, such as monotonicity, convexity, non-increasing (non-decreasing) returns to scale, or the Slutsky inequality of consumer theory; but economic theory does not provide finite-dimensional parametric models. This motivates nonparametric estimation under shape restrictions. Nonparametric estimates are often very noisy. Shape restrictions stabilize nonparametric estimates without imposing arbitrary restrictions, such as additivity or a single-index structure, that may be inconsistent with economic theory and the data. This paper explains how to estimate and obtain an asymptotic uniform confidence band for a conditional mean function under possibly nonlinear shape restrictions, such as the Slutsky inequality. The results of Monte Carlo experiments illustrate the finite-sample performance of the method, and an empirical example illustrates its use in an application.
Author : G.G Roussas
Publisher : Springer Science & Business Media
ISBN 13 : 9401132224
Total Pages : 691 pages
Book Rating : 4.4/5 (11 download)
Download or read book Nonparametric Functional Estimation and Related Topics written by G.G Roussas and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: About three years ago, an idea was discussed among some colleagues in the Division of Statistics at the University of California, Davis, as to the possibility of holding an international conference, focusing exclusively on nonparametric curve estimation. The fruition of this idea came about with the enthusiastic support of this project by Luc Devroye of McGill University, Canada, and Peter Robinson of the London School of Economics, UK. The response of colleagues, contacted to ascertain interest in participation in such a conference, was gratifying and made the effort involved worthwhile. Devroye and Robinson, together with this editor and George Metakides of the University of Patras, Greece and of the European Economic Communities, Brussels, formed the International Organizing Committee for a two week long Advanced Study Institute (ASI) sponsored by the Scientific Affairs Division of the North Atlantic Treaty Organization (NATO). The ASI was held on the Greek Island of Spetses between July 29 and August 10, 1990. Nonparametric functional estimation is a central topic in statistics, with applications in numerous substantive fields in mathematics, natural and social sciences, engineering and medicine. While there has been interest in nonparametric functional estimation for many years, this has grown of late, owing to increasing availability of large data sets and the ability to process them by means of improved computing facilities, along with the ability to display the results by means of sophisticated graphical procedures.
Author : Guangyi Ma
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (819 download)
Download or read book Three Essays on Estimation and Testing of Nonparametric Models written by Guangyi Ma and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, I focus on the development and application of nonparametric methods in econometrics. First, a constrained nonparametric regression method is developed to estimate a function and its derivatives subject to shape restrictions implied by economic theory. The constrained estimators can be viewed as a set of empirical likelihood-based reweighted local polynomial estimators. They are shown to be weakly consistent and have the same first order asymptotic distribution as the unconstrained estimators. When the shape restrictions are correctly specified, the constrained estimators can achieve a large degree of finite sample bias reduction and thus outperform the unconstrained estimators. The constrained nonparametric regression method is applied on the estimation of daily option pricing function and state-price density function. Second, a modified Cumulative Sum of Squares (CUSQ) test is proposed to test structural changes in the unconditional volatility in a time-varying coefficient model. The proposed test is based on nonparametric residuals from local linear estimation of the time-varying coefficients. Asymptotic theory is provided to show that the new CUSQ test has standard null distribution and diverges at standard rate under the alternatives. Compared with a test based on least squares residuals, the new test enjoys correct size and good power properties. This is because, by estimating the model nonparametrically, one can circumvent the size distortion from potential structural changes in the mean. Empirical results from both simulation experiments and real data applications are presented to demonstrate the test's size and power properties. Third, an empirical study of testing the Purchasing Power Parity (PPP) hypothesis is conducted in a functional-coefficient cointegration model, which is consistent with equilibrium models of exchange rate determination with the presence of trans- actions costs in international trade. Supporting evidence of PPP is found in the recent float exchange rate era. The cointegration relation of nominal exchange rate and price levels varies conditioning on the real exchange rate volatility. The cointegration coefficients are more stable and numerically near the value implied by PPP theory when the real exchange rate volatility is relatively lower.
Author : Alexandre B. Tsybakov
Publisher : Springer Science & Business Media
ISBN 13 : 0387790527
Total Pages : 222 pages
Book Rating : 4.3/5 (877 download)
Download or read book Introduction to Nonparametric Estimation written by Alexandre B. Tsybakov and published by Springer Science & Business Media. This book was released on 2008-10-22 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field.
Author : Timo Kuosmanen
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Stochastic Nonparametric Envelopment of Data written by Timo Kuosmanen and published by . This book was released on 2007 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of production frontier estimation is divided between the parametric Stochastic Frontier Analysis (SFA) and the deterministic, nonparametric Data Envelopment Analysis (DEA). This paper explores an amalgam of DEA and SFA that melds a nonparametric frontier with a stochastic composite error. Our model imposes the standard SFA assumptions for the inefficiency and noise terms. The frontier is estimated nonparametrically, imposing monotonicity and convexity as in DEA. For estimation, we propose two alternative methods based on shape constrained nonparametric least squares. The performance of the proposed estimation techniques is examined using Monte Carlo simulations and an illustrative application.
Author : Jeffrey S. Racine
Publisher : Cambridge University Press
ISBN 13 : 1108757286
Total Pages : 436 pages
Book Rating : 4.1/5 (87 download)
Download or read book An Introduction to the Advanced Theory and Practice of Nonparametric Econometrics written by Jeffrey S. Racine and published by Cambridge University Press. This book was released on 2019-06-27 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in nonparametric methodology has grown considerably over the past few decades, stemming in part from vast improvements in computer hardware and the availability of new software that allows practitioners to take full advantage of these numerically intensive methods. This book is written for advanced undergraduate students, intermediate graduate students, and faculty, and provides a complete teaching and learning course at a more accessible level of theoretical rigor than Racine's earlier book co-authored with Qi Li, Nonparametric Econometrics: Theory and Practice (2007). The open source R platform for statistical computing and graphics is used throughout in conjunction with the R package np. Recent developments in reproducible research is emphasized throughout with appendices devoted to helping the reader get up to speed with R, R Markdown, TeX and Git.
Author : Qi Li
Publisher : Emerald Group Publishing
ISBN 13 : 184950623X
Total Pages : 570 pages
Book Rating : 4.8/5 (495 download)
Download or read book Nonparametric Econometric Methods written by Qi Li and published by Emerald Group Publishing. This book was released on 2009-12-04 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains a selection of papers presented initially at the 7th Annual Advances in Econometrics Conference held on the LSU campus in Baton Rouge, Louisiana during November 14-16, 2008. This work is suitable for those who wish to familiarize themselves with nonparametric methodology.
Author : A.J. Tallón-Ballesteros
Publisher : IOS Press
ISBN 13 : 1643683012
Total Pages : 498 pages
Book Rating : 4.6/5 (436 download)
Download or read book Modern Management Based on Big Data III written by A.J. Tallón-Ballesteros and published by IOS Press. This book was released on 2022-09-29 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is the basic ingredient of all Big Data applications, and Big Data technologies are constantly deploying new strategies to maximise efficiency and reduce the time taken to process information. This book presents the proceedings of MMBD2022, the third edition of the conference series Modern Management based on Big Data (MMBD). The conference was originally scheduled to take place from 15 to 18 August 2022 in Seoul, South Korea, but was changed to a virtual event on the same dates. Some 200 submissions were received for presentation at the conference, 52 of which were ultimately accepted after exhaustive review by members of the programme committee and peer-reviewers, who took into account the breadth and depth of the research topics and the scope of MMBD. Topics covered include data analytics, modelling, technologies and visualization, architectures for parallel processing systems, data mining tools and techniques, machine learning algorithms, and big data for engineering applications. There are also papers covering modern management, including topics such as strategy, decision making, manufacturing and logistics-based systems, engineering economy, information systems and law-based information treatment, and papers from a special session covering big data in manufacturing, retail, healthcare, accounting, banking, education, global trading, and e-commerce. Big data analysis and emerging applications were popular topics. The book includes many innovative and original ideas, as well as results of general significance, all supported by clear and rigorous reasoning and compelling evidence and methods, and will be of interest to all those working with Big Data.
Author : Joachim Freyberger
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (84 download)
Download or read book Identification and Shape Restrictions in Nonparametric Instrumental Variables Estimation written by Joachim Freyberger and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper is concerned with inference about an unidentified linear functional, L(g), where the function g satisfies the relation Y=g(x) + U; E(U/W) = 0. In this relation, Y is the dependent variable, X is a possibly endogenous explanatory variable, W is an instrument for X, and U is an unobserved random variable. The data are an independent random sample of (Y, X, W). In much applied research, X and W are discrete, and W has fewer points of support than X. Consequently, neither g nor L(g) is nonparametrically identified. Indeed, L(g) can have any value in ( -oo, oo). In applied research, this problem is typically overcome and point identification is achieved by assuming that g is a linear function of X. However, the assumption of linearity is arbitrary. It is untestable if W is binary, as is the case in many applications. This paper explores the use of shape restrictions, such as monotonicity or convexity, for achieving interval identification of L(g). Economic theory often provides such shape restrictions. This paper shows that they restrict L(g) to an interval whose upper and lower bounds can be obtained by solving linear programming problems. Inference about the identified interval and the functional L(g) can be carried out by using by using the bootstrap. An empirical application illustrates the usefulness of shape restrictions for carrying out nonparametric inference about L(g).
Author : Subal C. Kumbhakar
Publisher : Cambridge University Press
ISBN 13 : 1107029511
Total Pages : 375 pages
Book Rating : 4.1/5 (7 download)
Download or read book A Practitioner's Guide to Stochastic Frontier Analysis Using Stata written by Subal C. Kumbhakar and published by Cambridge University Press. This book was released on 2015-02-02 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides practitioners with a step-by-step guide on how to conduct efficiency analysis using the stochastic frontier approach.
Author : Ali Emrouznejad
Publisher : Springer Nature
ISBN 13 : 3031615891
Total Pages : 399 pages
Book Rating : 4.0/5 (316 download)
Download or read book Business Analytics and Decision Making in Practice written by Ali Emrouznejad and published by Springer Nature. This book was released on with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : B. L. S. Prakasa Rao
Publisher : Academic Press
ISBN 13 : 148326923X
Total Pages : 539 pages
Book Rating : 4.4/5 (832 download)
Download or read book Nonparametric Functional Estimation written by B. L. S. Prakasa Rao and published by Academic Press. This book was released on 2014-07-10 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonparametric Functional Estimation is a compendium of papers, written by experts, in the area of nonparametric functional estimation. This book attempts to be exhaustive in nature and is written both for specialists in the area as well as for students of statistics taking courses at the postgraduate level. The main emphasis throughout the book is on the discussion of several methods of estimation and on the study of their large sample properties. Chapters are devoted to topics on estimation of density and related functions, the application of density estimation to classification problems, and the different facets of estimation of distribution functions. Statisticians and students of statistics and engineering will find the text very useful.
Author : Sam Efromovich
Publisher : CRC Press
ISBN 13 : 1351679848
Total Pages : 448 pages
Book Rating : 4.3/5 (516 download)
Download or read book Missing and Modified Data in Nonparametric Estimation written by Sam Efromovich and published by CRC Press. This book was released on 2018-03-12 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic types of missing at random and not at random, biasing, truncation, censoring, and measurement errors are discussed, and their treatment is explained. Ten chapters of the book cover basic cases of direct data, biased data, nondestructive and destructive missing, survival data modified by truncation and censoring, missing survival data, stationary and nonstationary time series and processes, and ill-posed modifications. The coverage is suitable for self-study or a one-semester course for graduate students with a prerequisite of a standard course in introductory probability. Exercises of various levels of difficulty will be helpful for the instructor and self-study. The book is primarily about practically important small samples. It explains when consistent estimation is possible, and why in some cases missing data should be ignored and why others must be considered. If missing or data modification makes consistent estimation impossible, then the author explains what type of action is needed to restore the lost information. The book contains more than a hundred figures with simulated data that explain virtually every setting, claim, and development. The companion R software package allows the reader to verify, reproduce and modify every simulation and used estimators. This makes the material fully transparent and allows one to study it interactively. Sam Efromovich is the Endowed Professor of Mathematical Sciences and the Head of the Actuarial Program at the University of Texas at Dallas. He is well known for his work on the theory and application of nonparametric curve estimation and is the author of Nonparametric Curve Estimation: Methods, Theory, and Applications. Professor Sam Efromovich is a Fellow of the Institute of Mathematical Statistics and the American Statistical Association.
Author : Pedro Macedo
Publisher : Springer Nature
ISBN 13 : 3031295838
Total Pages : 267 pages
Book Rating : 4.0/5 (312 download)
Download or read book Advanced Mathematical Methods for Economic Efficiency Analysis written by Pedro Macedo and published by Springer Nature. This book was released on 2023-06-21 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic efficiency analysis has received considerable worldwide attention in the last few decades, with Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA) establishing themselves as the two dominant approaches in the literature. This book, by combining cutting-edge theoretical research on DEA and SFA with attractive real-world applications, offers a valuable asset for professors, students, researchers, and professionals working in all branches of economic efficiency analysis, as well as those concerned with the corresponding economic policies. The book is divided into three parts, the first of which is devoted to basic concepts, making the content self-contained. The second is devoted to DEA, and the third to SFA. The topics covered in Part 2 range from stochastic DEA to multidirectional dynamic inefficiency analysis, including directional distance functions, the elimination and choice translating algorithm, benefit-of-the-doubt composite indicators, and internal benchmarking for efficiency evaluations. Part 3 also includes exciting and cutting-edge theoretical research on e.g. robustness, nonparametric stochastic frontier models, hierarchical panel data models, and estimation methods like corrected ordinary least squares and maximum entropy.
