Kantorovich inequalities and efficiency comparisons for several classes of estimators in linear models

S. Liu, H. Neudecker

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

New matrix, determinant and trace versions of the Kantorovich inequality (KI) involving two positive definite matrices are presented. Some of these are used to study the efficiencies of minimum-distance (MD) estimators, generalized method-of-moments (GMM) estimators and several estimators specific to longitudinal or panel-data analysis. They are also used to give upper bounds for the determinant and trace of the asymptotic variance matrix of a weighted least-squares (WLS) estimator in the generalized linear model.

Original languageEnglish
Pages (from-to)345-355
Number of pages11
JournalStatistica Neerlandica
Volume51
Issue number3
DOIs
Publication statusPublished - 1 Jan 1997
Externally publishedYes

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Kantorovich Inequality
Linear Model
Determinant
Trace
Minimum Distance Estimator
Weighted Least Squares Estimator
Estimator
Generalized Method of Moments
Moment Estimator
Positive definite matrix
Panel Data
Asymptotic Variance
Generalized Linear Model
Longitudinal Data
Data analysis
Upper bound
Class

Cite this

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abstract = "New matrix, determinant and trace versions of the Kantorovich inequality (KI) involving two positive definite matrices are presented. Some of these are used to study the efficiencies of minimum-distance (MD) estimators, generalized method-of-moments (GMM) estimators and several estimators specific to longitudinal or panel-data analysis. They are also used to give upper bounds for the determinant and trace of the asymptotic variance matrix of a weighted least-squares (WLS) estimator in the generalized linear model.",
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Kantorovich inequalities and efficiency comparisons for several classes of estimators in linear models. / Liu, S.; Neudecker, H.

In: Statistica Neerlandica, Vol. 51, No. 3, 01.01.1997, p. 345-355.

Research output: Contribution to journalArticle

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AU - Neudecker, H.

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KW - Generalized method-of-moments estimators

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