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Dynamic Systems in Management Science explores the important gaps in the existing literature on operations research and management science by providing new and operational methods which are tested in practical environment and a variety of new applications. Also, some novel techniques and methods are presented, like the relevant p-values of lower and upper limits to test first order autocorrelation in such a way that the Durbin-Watson tables used for this purpose become redundant. Further, the computation of the revised condition number to efficiently detect multicollinearity, a simple and robust method to detect the degree of integration of a given series, another one to compute co-integration vectors using the generalized inverse approach and additionally to solve a linear optimal control problem with quadratic cost functional, using the properties of the generalized inverse, are some of the subjects not seen in relevant books.