Zusammenfassung
Der Einbezug zufälliger oder stochastischer Einflüsse in ein Simulation ist nicht immer notwendig und auf jeden Fall zu vermeiden, wenn dies möglich ist. Es gibt aber viele Probleme, bei denen gerade der Zufall, die unregelmässigen Schwankungen, die Unsicherheit, die nicht vollständige Voraussagbarkeit der Phänomene das Wesentliche ist. Typische Beispiele sind Warteschlangen-Pänomene, die gar nicht mehr existieren, wenn der Zufall eliminiert wird.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Literatur
Ahrens, J.H.; Dieter U.; Grube, A.; Pseudo-random numbers, a new proposal for the choice of multiplicators. Computing 6, (1970), 121–138.
Ahrens, J.H.; Dieter, U.; Computer methods for sampling from the exponential and normal distribution. Comm. ACM 15, (1972).
Anderson, T.W.; An introduction to multivariate Statistical analysis. J. Wiley, New York, 1958.
Anderson, T.W.;The Statistical analysis of time series. J. Wiley, New York, 1971.
Box, G.E.P.; Muller, M.E.; A note on the generation of random normal deviates. Ann. Math. Stat. 29, (1958), 610–611.
Box, G.E.P.; Jenkins, G.M.; Time series analysis: forecasting and control. Holden-Day, San Francisco, 1970.
Dieter, U.; An exact determination of serial correlations of pseudo-random numbers. Numer.Math. 17, (1971), 101–123.
Dieter, U.; Pseudo-random numbers: the exact distribution of pairs. Math. Comp. 25, (1971), 855–883.
Greenberger, M.; An ä priori determination of serial correlations in Computer generated random numbers. Math. Comp. 15, (1961), 383–389.
Fishman, G.S.; Kiviat, P.J.; The analysis of Simulation generated time series. Man.Sei. 13, (1967), 525–557.
Fishman, G.S.; Estimating sample size in Computer Simulation experiments. Man.Sei. 18, (1971), 21–38.
Fishman, G.S.; A study of bias considerations in Simulation experiments. Operations Res. 20, (1972), 785–790.
Fishman, G.S.; Concepts and methods in discrete event digital Simulation. J. Wiley, New York, 1973.
Gavarian, A.V.; Ancker, C.J.; Mean value estimation from digital Computer Simulation. Operations Res. 14, (1966), 25–44.
Gnedenke, B.W.; Lehrbuch der Wahrscheinlichkeitsrechnung. Akademie-Verlag, Berlin, 1962.
Hammersley, J.M.; Handscomb,D.C.; Monte Carlo methods, Methuen, London, 1964.
Handscomb, D.C.; Monte Carlo techniques: theoretical, in 36.
Helm, M.; Statistical analysis of Simulation results by UNISIAS. Compstat 1974, proc. in computational statistics, Physica, Wien, 1974.
Hull, T.E.; Dobell, A.R.; Random number generators. SIAM review 4, (1962), 230–254.
IBM; General purpose Simulation system/360, User’s manual, H20-0326-0.
IBM; SIMPL/I (Simulations language based on PL/I) Program reference manual. SH 19-5060-0.
Kleijnen, J.P.; Monte Carlo techniques: a comment, in 36.
Knuth, D.E.; The art of Computer programming. Vol 2: seminumerical algorithms. Chap. 3. Addison-Wesely, Reading, Mass., 1969.
Kohlas, J.; Die Monte Carlo Methode. In Bauknecht, K.; Nef, W. (Herausg.); Digitale Simulation. Lecture Notes in O.R. and Math. Systems 51. Springer, Berlin, 1971.
Kohlas, J.; Monte Carlo Simulation in Operations Research. Lecture Notes in Economics and Math. Systems 63. Springer, Berlin, 1972.
Kohlas, J.; Variance reducing two-stage procedures for the Monte Carlo analysis of Markov chains. Compstat 1974, proc. in computational statistics, Physica, Wien, 1974.
Kotler, Ph.;Marketing decision making, a model building approach. Holt, Rinehart and Winston, 1971.
Krasnow, H.S.; Simulation languages, in 36.
Lehmer, D.H.; Mathematical methods in large scale digital calcul. machinery. Harvard Univ. Press, (1949), 141-146.
Lilliefors, H.W.; On the Kolmogorov-Smirnov test for normality with mean and variance unknown. J. Am. Stat. Ass. 62, (1967), 399–402.
Lilliefors, H.W.; On the Kolmogorov-Smirnov test for exponential distribution with mean unknown. J. Am.Stat.Ass. 64, (1969), 387–389.
MacLaren, M.D.; Marsaglia, G.; Uniform random number generators. J. ACM 12, (1965), 83–89.
Marsaglia, G.; Random variables and Computers. Trans.Third Prague Conf. Inf. Theory; Publ. House Czech. Acad. Sei. Prag, (1964), 499-512.
Marsaglia, G.; Random numbers fall mainly in the planes. Proc. Natl. Acad. Sei. 61, (1968), 83–89.
Moay, W.A.; Monte Carlo techniques: practical, in 36.
Naylor, Th.H.; (Ed.); The design of Computer Simulation experiments. Duke Univ. Press, 1969.
Rohlfing, H.; SIMULA, eine Einführung. BI Hochschultaschenbücher, Bd. 747.
Salfi, R.; A long-period random number generator with application to permutations. Compstat 1974, proc. in computational statistics. Physica, Wien, 1974.
Scheffe, H.; The analysis of variance. J. Wiley, New York, 1959.
Van der Waerden, B.L.; Mathematische Statistik. Springer, Berlin, 1965.
Wilks, S.S.; Mathematical Statistics. J. Wiley, New York, 1962.
Raiffa, H.; Decision Analysis, Introductory Lectures on Choices under Uncertainity. Addison - Wesely, Reading, Mass., 1968.
Kleijnen, J.P.C.; Statistical Techniques in Simulation, Part I. Statistics: Textbooks and Monographs, Vol. 9. Marcel Dekker, New York, 1974.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1976 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Bauknecht, K., Kohlas, J., Zehnder, C.A. (1976). Simulation stochastischer Experimente und statistische Auswertung von Simulations-Versuchen. In: Simulationstechnik. Hochschultext. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-66501-1_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-66501-1_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-07960-6
Online ISBN: 978-3-642-66501-1
eBook Packages: Springer Book Archive