Constructing the confidence intervals and areas for a multiple linear regression model using bayesian scientific approach

R.Z. Khayrullin1,2

1Moscow State (National Research) University of Civil Engineering, Moscow, Russia
2FSBI «MSMC» of the Ministry of Defense of the Russian Federation, Moscow, Russia

Al’manac of Modern Metrology № 4 (28) 2021, pages 170–185

Annotation. An algorithm for constructing point and interval statistical estimates for the parameters of the multiple linear regression model is presented. The results of comparison with the corresponding estimates obtained by the classical maximum likelihood method are presented. The proposed algorithm can be effectively applied in the development of microwave measurement techniques on vector network analyzers, in the development of practical methods for detecting systematic measurement errors, in correcting measurement results.

Key words: measurement accuracy, Bayesian scientific approach, a posteriori information.

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