Under military war weapon support the economic bond level estimation using generalized Petersen graph with imputation

Several countries of the world are involved in mutual and collaborative business military equipments, weapons terms their production, sales, technical maintenance, training services. As a consequence, manufacturing boms, rockets, missiles other ammunitions have taken structured smooth shape to help others where when needed. Often support among remain open for information media, but sometime secret due national security international political pressure. Such phenomenon (hidden or ) is part supply chain could be modeled like Petersen graph considering vertices as edges economic bonds. For large graphical structure, without sampling, it difficult find out average bonding (open & secret) between any pair support. This paper presents sample based estimation methodology estimating mean bond value business. Motivation problem derived from current Russia-Ukraine war situation kind hidden by NATO countries. A node sampling procedure proposed whose bias, mean-squared error properties derived. Results supported with empirical studies. Findings compared particular cases confidence intervals used basic tool comparison. Pattern imputation together new proposal CIImputation method who has been proved useful filling missing value, specially data found missing. The undergoing Ukraine Russia weapon, an application contained this paper. Key words: Graph, Estimator, Bias, Mean Squared Error (MSE), Optimum Choice, Confidence (CI), Nodes (vertices), Imputation, CI-Imputation (LLimputation UL-imputation), Economic Bonds, Military War, Weapon Support