Multivariate Data Imputation using Trees

We address the problem of completing two files with records containing a fully observed common subset of variables. The tecnique investigated involves the use of regression and/or classification trees. An extension of current methodology (the intersection-seeking or "forest-climbing" algorithm) is proposed to deal with multivariate response variables. The method is demonstrated and shown to be feasible and have some desirable properties.

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Year of publication:	2002
Authors:	Palmer, Tusell ; Jorge, Fernando ; Ruiz, Bárcena ; Jesús, María
Institutions:	Departamento de Economía Aplicada III (Econometría y Estadística), Facultad de Ciencias Económicas y Empresariales
Subject:	file completion \| data imputation \| regression trees

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Extent:	application/pdf
Series:	BILTOKI.
Type of publication:	Book / Working Paper
Language:	English
Notes:	The text is part of a series Biltoki 2002.05 Number 2002-05
Classification:	C14 - Semiparametric and Nonparametric Methods ; C12 - Hypothesis Testing
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005157580