1997-01-15Buch DOI: 10.18452/3796
Nonparametric Kernel and Regression Spline Estimation in the Presence of Measurement Error
 dc.contributor.author Maca, J. D. dc.contributor.author Carroll, Raymond J. dc.contributor.author Ruppert, David dc.date.accessioned 2017-06-15T22:08:58Z dc.date.available 2017-06-15T22:08:58Z dc.date.created 2006-05-18 dc.date.issued 1997-01-15 dc.identifier.issn 1436-1086 dc.identifier.uri http://edoc.hu-berlin.de/18452/4448 dc.description.abstract In many regression applications both the independent and dependent variables are measured with error. When this happens, conventional parametric and nonparametric regression techniques are no longer valid. We consider two different nonparametric techniques, regression splines and kernel estimation, of which both can be used in the presence of measurement error. Within the kernel regression context, we derive the limit distribution of the SIMEX estimate. With the regression spline technique, two different methods of estimations are used. The first method is the SIMEX algorithm which attempts to estimate the bias, and remove it. The second method is a structural approach, where one hypothesizes a distribution for the independent variable which depends on estimable parameters. A series of examples and simulations illustrate the methods. eng dc.language.iso eng dc.publisher Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät dc.rights.uri http://rightsstatements.org/vocab/InC/1.0/ dc.subject Bootstrap eng dc.subject Measurement Error eng dc.subject Local Polynomial Regression eng dc.subject SIMEX eng dc.subject Asymptotic theory eng dc.subject Estimating Equations eng dc.subject Nonlinear Regression eng dc.subject Bandwidth Selection eng dc.subject Regression Splines eng dc.subject Sandwich Estimation eng dc.subject.ddc 330 Wirtschaft dc.title Nonparametric Kernel and Regression Spline Estimation in the Presence of Measurement Error dc.type book dc.identifier.urn urn:nbn:de:kobv:11-10063710 dc.identifier.doi http://dx.doi.org/10.18452/3796 dc.subject.dnb 17 Wirtschaft local.edoc.pages 17 local.edoc.type-name Buch local.edoc.container-type series local.edoc.container-type-name Schriftenreihe local.edoc.container-year 1997 dc.identifier.zdb 2135319-0 bua.series.name Sonderforschungsbereich 373: Quantification and Simulation of Economic Processes bua.series.issuenumber 1997,11