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Analysis of the terrestrial pole coordinates using regression dynamic modeling© SGEM 2018. For processing observations of the terrestrial pole dynamics, the regression dynamic
RESEARCH OF DEPENDENCE OF THE MAIN MACROECONOMIC INDICATORS BY MEANS OF THE CORRELATION AND REGRESSION ANALYSISUsing the correlation and regression analysis the research of relations between macroeconomic
Using Additive Robust Modeling and Fault Simulation for Laser Ranging Measurements© 2020 IEEE. This paper is focusing on the application of the regression modeling for analyzing
IREB2, CHRNA5, CHRNA3, FAM13A & HEDGEHOG INTERACTING PROTEIN GENES POLYMORPHISMS & RISK OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE IN TATAR POPULATION FROM RUSSIA models. Linear regression analyses were performed to estimate the relationship between SNPs and lung
IREB2, CHRNA5, CHRNA3, FAM13A & HEDGEHOG INTERACTING PROTEIN GENES POLYMORPHISMS & RISK OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE IN TATAR POPULATION FROM RUSSIA models. Linear regression analyses were performed to estimate the relationship between SNPs and lung
Therapeutic drug monitoring of levetiracetam in newborns ideal pharmacokinetic profile: linear pharmacokinetics, predictable doseconcentration relationship, wide
Inflammatory and Immune Response Genes Polymorphisms are Associated with Susceptibility to Chronic Obstructive Pulmonary Disease in Tatars Population from Russia, Russia). Logistic regression was used to detect the association of SNPs in different models. Linear
Swing-By Applications and Estimation of the Van Allen Belts’ Radiation Exposure for a Spacecraft in a Low Thrust Transfer to the Moon eccentricity and the propulsion system’s characteristics. Then, a multi-linear regression and an artificial
The implementation of the concept of individualization in training elite female athletes with visual impairment in the sprint analysis was carried out using the main components method with Varimax rotation, multiple regression
Management of a sustainable development of the oil and gas sector in the context of digitalization of environmental friendliness of the oil and gas sector. As a result, a linear regression model is proposed
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