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2009•Journal of Hefei University of TechnologyRequires access

A seemingly unrelated regression model with MA error structure in credibility framework

WU Xian-yi

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Abstract

The commonly used credibility regression models often deal with one-dimensional observation data.In this paper,multi-dimensional regression models are discussed,and an SUR model with an additional moving average error structure in the credibility framework is presented.A method for estimating unknown parameters is proposed.Simulations are performed to illustrate that the proposed method is feasible.

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What this paper is about

The commonly used credibility regression models often deal with one-dimensional observation data.In this paper,multi-dimensional regression models are discussed,and an SUR model with an additional moving average error structure in the credibility framework is presented.A method for estimating unknown parameters is proposed.Simulations are performed to illustrate that the proposed method is feasible.

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Available abstract

The commonly used credibility regression models often deal with one-dimensional observation data.In this paper,multi-dimensional regression models are discussed,and an SUR model with an additional moving average error structure in the credibility framework is presented.A method for estimating unknown parameters is proposed.Simulations are performed to illustrate that the proposed method is feasible.

Key concepts: Credibility, Seemingly unrelated regressions, Regression, Regression analysis, Econometrics, Computer science, Errors-in-variables models, Statistics

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