Similar-sounding problems have been attacked through a technique that
uses a much simpler algorithm and goes under many different names.
See -ipf- and -mstdize- on SSC and any encyclopaedic survey of
categorical data analysis.
Nick
[email protected]
Andreas Peichl
I'm interested in re-weighting a microdata sample to fit aggregate
control
data based on the Minimum Information Loss (MIL) principle (see Merz
1994).
Based on information theory this principle satisfies the desired
positivity
constraint on the weighting factors to be computed. For the consistent
solution which simultaneously adjusts hierarchical microdata (e.g.
household
and personal information), a fast numerical solution by a specific
modified
Newton-Raphson (MN) procedure with a global exponential approximation is
proposed by Merz (1994).
This procedure involes numerically solving of a set of non-linear
equations.
I'm aware of
http://www.stata.com/support/faqs/lang/nl.html.
I was wondering if it were possible to solve a set of non-linear
equations
with Mata (So far, I have't used Mata but I'd like to invest the time to
learn it if it helps me solving this problem)? If yes, any hints on how
to
tackle this problem are highly appreciated.
Does somebody know any other programs for Stata/Mata that allow
reweighting
of microdata?
Merz, Joachim (1994): Microdata Adjustment by the Minimum Information
Loss
Principle. Unpublished.
http://mpra.ub.uni-muenchen.de/7231/
--------------------------------------------------------
Dr. Andreas Peichl
Research Associate
IZA - Forschungsinstitut zur Zukunft der Arbeit GmbH
IZA - Institute for the Study of Labor
P.O. Box 7240, 53072 Bonn, Germany
Schaumburg-Lippe-Str. 5-9, 53113 Bonn, Germany
Phone: +49 (228) 3894-511; Fax: +49 (228) 3894-510
E-Mail: [email protected]
Web: http://www.iza.org
Registered Office Bonn, District Court of Bonn, HRB 7745
Represented by: Prof. Dr. Klaus F. Zimmermann (Director)
--------------------------------------------------------
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