AAAI Publications, Twenty-First International Joint Conference on Artificial Intelligence

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Parameter Identification in a Class of Linear Structural Equation Models
Jin Tian

Last modified: 2009-06-26

Abstract


Linear causal models known as structural equation models (SEMs) are widely used for data analysis in the social sciences, economics, and artificial intelligence, in which random variables are assumed to be continuous and normally distributed. This paper deals with one fundamental problem in the applications of SEMs -- parameter identification. The paper uses the graphical models approach and provides a procedure for solving the identification problem in a special class of SEMs.

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