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Regular version of the site

Article

Optimality of Multiple Decision Statistical Procedure for Gaussian Graphical Model Selection

Lecture Notes in Computer Science. 2019. No. 11353. P. 304-308.

Gaussian graphical model selection is a statistical problem

that identifies the Gaussian graphical model from observations. Existing

Gaussian graphical model selection methods focus on the error rate

for incorrect edge inclusion. However, when comparing statistical procedures,

it is also important to take into account the error rate for

incorrect edge exclusion. To handle this issue we consider the graphical

model selection problem in the framework of multiple decision theory.We

show that the statistical procedure based on simultaneous inference with

UMPU individual tests is optimal in the class of unbiased procedures.