Recursive estimation of origin-destination matrices from input/output counts |
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| Institution: | 1. Dipartimento di Economia Politica e Statistica, Università degli Studi di Siena, Siena, Italy;2. Dipartimento di Economia e Finanza, LUISS University, Rome, Italy;1. Department of Civil Engineering, International University – VNU HCMC, Viet Nam;2. Faculty of Applied Mechanics and Civil Engineering, University of Technical Education – HCMC, Viet Nam;1. Department of Finance and Control Sciences, School of Mathematical Sciences, Fudan University, Shanghai 200433, China;2. Department of Mathematics, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany;1. University of Trento, Department of Mathematics, Via Sommarive, 14, Trento, 38123, Italy;2. University of Verona, Department of Computer Science, Strada le Grazie, 15, Verona, 37134, Italy;1. Department of Anesthesiology, The First Affiliated Hospital of the General Hospital of CPLA, Beijing 100048, China;2. Department of Anesthesiology, The General Hospital of CPLA, Beijing 100853, China |
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| Abstract: | The application of recursive prediction error techniques to the problem of estimating origin-destination patterns from input and output volume counts is described. Each algorithm deals with the special case where route choice between origin and destination can be ignored. A gradient algorithm developed by Cremer and Keller (1983) turns out to be a special case of a family of methods described by Ljung and Söderström (1983). After describing how the methods developed in Ljung and Söderström (1983) could be modified so that the resulting estimates satisfy natural constraints, a number of algorithm possibilities are tested. Generally, those algorithms employing Gauss-Newton search directions appear superior to gradient-based methods, while the constraining procedures improve accuracy. |
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