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- W4252249648 abstract "Vector autoregressive processes of the first order are considered which are non-negative and optimize a linear objective function. These processes may be used in stochastic linear programming with a dynamic structure. By using Tweedie's results from the theory of Markov chains, conditions for geometric rates of convergence to stationarity (i.e. so-called geometric ergodicity) and for existence and geometric convergence of moments of these processes are obtained." @default.
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- W4252249648 date "1988-06-01" @default.
- W4252249648 modified "2023-09-30" @default.
- W4252249648 title "Autoregressive processes in optimization" @default.
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- W4252249648 doi "https://doi.org/10.1017/s0021900200040948" @default.
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