Finite and Large Sample Distribution-free Inference in Median Regressions with Instrumental Variables
Author : Elise Coudin
Publisher :
Page : 49 pages
File Size : 45,59 MB
Release : 2010
Category :
ISBN :
Author : Elise Coudin
Publisher :
Page : 49 pages
File Size : 45,59 MB
Release : 2010
Category :
ISBN :
Author : Elise Coudin
Publisher :
Page : 57 pages
File Size : 15,69 MB
Release : 2007
Category :
ISBN :
Author : Donald W. K. Andrews
Publisher :
Page : 26 pages
File Size : 22,22 MB
Release : 2005
Category :
ISBN :
Author : J. S. Maritz
Publisher : Springer
Page : 282 pages
File Size : 30,2 MB
Release : 1981
Category : Mathematics
ISBN :
Basic concepts in distribution-free methods; One-sample location problems; Miscellaneous one-sample problems; Two-sample problems; Straight-line regression; Multiple regression and general linear models; Bivariate problems; Appendix; Bibliography.
Author : Jean-Marie Dufour
Publisher :
Page : 33 pages
File Size : 12,76 MB
Release : 1999
Category :
ISBN :
Author : Dufour, Jean-Marie
Publisher : Montréal : Université de Montréal, Centre de recherche et développement en économique
Page : 33 pages
File Size : 45,61 MB
Release : 1997
Category :
ISBN : 9782893823676
Author : James Joseph Heckman
Publisher : Elsevier
Page : 1013 pages
File Size : 24,13 MB
Release : 2007
Category : Econometrics
ISBN : 0444506314
As conceived by the founders of the Econometric Society, econometrics is a field that uses economic theory and statistical methods to address empirical problems in economics. It is a tool for empirical discovery and policy analysis. The chapters in this volume embody this vision and either implement it directly or provide the tools for doing so. This vision is not shared by those who view econometrics as a branch of statistics rather than as a distinct field of knowledge that designs methods of inference from data based on models of human choice ...
Author : Dufour, Jean-Marie
Publisher : Montréal : CIRANO
Page : 25 pages
File Size : 48,56 MB
Release : 2000
Category :
ISBN : 9782893823966
Author : Andrew Gelman
Publisher : CRC Press
Page : 677 pages
File Size : 40,83 MB
Release : 2013-11-01
Category : Mathematics
ISBN : 1439840954
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Author : Andrew Gelman
Publisher : Cambridge University Press
Page : 551 pages
File Size : 39,38 MB
Release : 2020-07-23
Category : Business & Economics
ISBN : 110702398X
A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference.