Comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters

We consider a regression of y on x given by a pair of mean and variance functions with a parameter vector θ to be estimated that also appears in the distribution of the regressor variable x. The estimation of θ is based on an extended quasi score (QS) function. Of special interest is the case where...

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Date:2007
Main Authors: Kukush, A., Malenko, A., Schneeweiss, H.
Format: Article
Language:English
Published: Інститут математики НАН України 2007
Online Access:https://nasplib.isofts.kiev.ua/handle/123456789/4514
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Journal Title:Digital Library of Periodicals of National Academy of Sciences of Ukraine
Cite this:Comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters / A. Kukush, A. Malenko, H. Schneeweiss // Theory of Stochastic Processes. — 2007. — Т. 13 (29), № 4. — С. 69–81. — Бібліогр.: 11 назв.— англ.

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Digital Library of Periodicals of National Academy of Sciences of Ukraine
id nasplib_isofts_kiev_ua-123456789-4514
record_format dspace
spelling Kukush, A.
Malenko, A.
Schneeweiss, H.
2009-11-24T15:27:02Z
2009-11-24T15:27:02Z
2007
Comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters / A. Kukush, A. Malenko, H. Schneeweiss // Theory of Stochastic Processes. — 2007. — Т. 13 (29), № 4. — С. 69–81. — Бібліогр.: 11 назв.— англ.
0321-3900
https://nasplib.isofts.kiev.ua/handle/123456789/4514
We consider a regression of y on x given by a pair of mean and variance functions with a parameter vector θ to be estimated that also appears in the distribution of the regressor variable x. The estimation of θ is based on an extended quasi score (QS) function. Of special interest is the case where the distribution of x depends only on a subvector α of θ, which may be considered a nuisance parameter. A major application of this model is the classical measurement error model, where the corrected score (CS) estimator is an alternative to the QS estimator. Under unknown nuisance parameters we derive conditions under which the QS estimator is strictly more аfficient than the CS estimator. We focus on the loglinear Poisson, the Gamma, and the logit model.
Alexander Kukush is supported by the Swedish Institute grant SI-01424/2007.
en
Інститут математики НАН України
Comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters
Article
published earlier
institution Digital Library of Periodicals of National Academy of Sciences of Ukraine
collection DSpace DC
title Comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters
spellingShingle Comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters
Kukush, A.
Malenko, A.
Schneeweiss, H.
title_short Comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters
title_full Comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters
title_fullStr Comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters
title_full_unstemmed Comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters
title_sort comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters
author Kukush, A.
Malenko, A.
Schneeweiss, H.
author_facet Kukush, A.
Malenko, A.
Schneeweiss, H.
publishDate 2007
language English
publisher Інститут математики НАН України
format Article
description We consider a regression of y on x given by a pair of mean and variance functions with a parameter vector θ to be estimated that also appears in the distribution of the regressor variable x. The estimation of θ is based on an extended quasi score (QS) function. Of special interest is the case where the distribution of x depends only on a subvector α of θ, which may be considered a nuisance parameter. A major application of this model is the classical measurement error model, where the corrected score (CS) estimator is an alternative to the QS estimator. Under unknown nuisance parameters we derive conditions under which the QS estimator is strictly more аfficient than the CS estimator. We focus on the loglinear Poisson, the Gamma, and the logit model.
issn 0321-3900
url https://nasplib.isofts.kiev.ua/handle/123456789/4514
citation_txt Comparing the efficiency of estimates in concrete errors-in-variables models under unknown nuisance parameters / A. Kukush, A. Malenko, H. Schneeweiss // Theory of Stochastic Processes. — 2007. — Т. 13 (29), № 4. — С. 69–81. — Бібліогр.: 11 назв.— англ.
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AT malenkoa comparingtheefficiencyofestimatesinconcreteerrorsinvariablesmodelsunderunknownnuisanceparameters
AT schneeweissh comparingtheefficiencyofestimatesinconcreteerrorsinvariablesmodelsunderunknownnuisanceparameters
first_indexed 2025-12-07T15:29:53Z
last_indexed 2025-12-07T15:29:53Z
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