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"In their OR (Operations Research) curricula, most universities place a lot of empha- sis on teaching algorithms for solving a variety of standard mathematical models for solving optimum decision-making problems like linear programming, nonlin- ear programming, integer programming, etc. and the mathematical analysis of their convergence properties and computational complexity. But they do not put much emphasis on helping their students cultivate the essential skill of constructing an appropriate mathematical model for real world decision-making problems, before these algorithms can be applied to solve them."

"This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications."