Abstract
If the dictionary definition were the sole criterion, a model would be considered valid if it was found to be well grounded, sound, cogent, logical, and incontestable. Similarly, a model would be deemed credible if it was deserving of or entitled to belief, or if it was plausible, tenable, or reasonable. All of these characteristics are, of course, desirable in a mathematical model of a physical system; but when used as the basis for the definition of model adequacy, they are clearly too subjective to provide useful and rigorous criteria for model evaluation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ackerman, B.A., Ackerman, S.R., Sawyer, J.W., and Henderson, D.W. (1974). The Uncertain Search for Environmental Quality. The Free Press, New York.
Barrett, J.F., Coales, J.F., Ledwich, M.A., Naughton, J.J., and Young, P.C. (1973). Macro-economic modeling: a critical appraisal. Proceedings of the IFAC/IFORS Conference on Dynamic Modelling and Control of National Economies. IEE, London.
Beck, M.B. and Young, P.C. (1975). A dynamic model for DO–BOD relationships in a non-tidal stream. Water Research, 9: 769–776.
Beer, T. and Young, P.C. (1980). On the Characterization of Longitudinal Dispersion in Natural Streams. Report No. AS/R42. Centre for Resource and Environmental Studies, Australian National University, Canberra.
Beer, T., Young, P.C., and Humphries, R.B. (1980). Murrumbidgee Water Quality Study: Report on CRES Contribution to the Study. Report No. AS/R41. Centre for Resource and Environmental Studies, Australian National University, Canberra.
Berlinski, D. (1976). On Systems Analysis. MIT Press, Cambridge, Massachusetts.
Bertrand, J. (1855). Méthode des Moindres Carrés, by K.F. Gauss. Translated into French by J. Bertrand. Mallet-Bachelur, Imprimeur-Libraire de L’Ecole Polytechnique, Paris.
Brewer, G.C. (1973). Politicians, Bureaucrats and the Consultant. Basic Books, New York.
Buffham, B.A. and Gibilaro, L.G. (1970). A unified time delay model for dispersion in flowing media. Chemical Engineering Journal, 1: 31–35.
Ellis, J., Kanamori, S., and Laird, P.G. (1977). Water pollution studies on Lake Illawarra. Australian Journal of Marine and Freshwater Research, 28: 467–477.
Fischer, H.B. (1966). A note on the one dimensional dispersion model. Air and Water Pollution, International Journal, 10: 443–452.
Fischer, H.B. (1968). Dispersion prediction in natural streams. Journal of Sanitation Engineering, ASCE, 94: 927–944.
Holling, C.S. (Editor) (1978). Adaptive Environmental Assessment and Management. Wiley, Chichester.
Hoos, I.R. (1972). Systems Analysis in Public Policy. University of California Press, Berkeley and Los Angeles.
Humphries, R.B., Young, P.C., and Beer, T. (1980). Systems Analysis of an Estuary; Report of the CRES Contribution to the Peel–Harvey Estuary Study. Bulletin No. 100, Western Australian Department of Conservation and Environment, Perth, Western Australia.
Jakeman, A.J. and Young, P.C. (1979a). Refined instrumental variable methods of recursive time series analysis. Part II: multivariable systems. International Journal of Control, 29: 621–644.
Jakeman, A.J. and Young, P.C. (1979b). Time-series methods in biological and medical data analysis. In R. Isermann (Editor), Identification and System Parameter Estimation. Pergamon Press, Oxford.
Jakeman, A.J. and Young, P.C. (1980). Towards optimal modeling of translocation data from tracer studies. Proceedings of the Biennial Conference of the Simulation Society of Australia, 4th, pp. 248–253.
Jakeman, A.J., Steele, L.P., and Young, P.C. (1980). Instrumental variable algorithms for multiple input systems described by multiple transfer functions. IEEE Transactions, Systems, Man, and Cybernetics, SMC-10: 593–602.
Johnston, J. (1963). Econometric Methods. McGraw-Hill, New York.
Kaldor, J.M. (1978). The Estimation of Parametric Change in Time-Series Models. M.A. Thesis, Australian National University, Canberra.
Kaiman, R.E. (1960). A new approach to linear filtering and prediction problems. ASME Transactions, Journal of Basic Engineering, 83D: 95–108.
Kendall, M.G. and Stuart, A. (1961). The Advanced Theory of Statistics, Volume 2. Griffin, London.
Kittler, J. and Young, P.C. (1973). A new approach to feature selection based on the Karhunen–Loeve expansion. Pattern Recognition, 5: 335–352.
Miller, D.R., Butler, G., and Bramall, C. (1976). Validation of ecological system models. Journal of Environmental Management, 4:383–401.
Philip, J.R. (1975). Some remarks on science and catchment prediction. In T.G. Chapman and F.X. Dunin (Editors), Prediction in Catchment Hydrology. Australian Academy of Science, Canberra.
Plackett, R.L. (1950). On some theorems in least squares. Biometrika, 37: 149–157.
Popper, K.R. (1959). The Logic of Scientific Discovery. Hutchinson, London.
Rademaker, O. (1973). On understanding complicated models: simple methods. Presented at the American/Soviet Conference on Methodological Aspects of Social Systems Simulation, Sukhumi (USSR), October 24–26.
Rigler, F.H (1976). Review of “Systems Analysis and Simulation in Ecology”, Volume 3. B.C. Patten (Editor), Limnology and Oceanography, 21 (3): 481–483.
Salmon, M. and Young, P.C. (1978). Control methods and quantitative economic policy. In S. Holly, B. Rustem, and M. Zarrop (Editors), Optimal Control for Econometric Models: An Approach to Economic Policy Formation. MacMillan, London.
Smith, R. (1980). Buoyancy effects upon longitudinal dispersion in wide well-mixed estuaries. Philosophical Transactions of the Royal Society, Series A, 296:467–496.
Spear, R.C. (1970). Application of Kolmogorov–Renyi statistics to problems of parameter uncertainty in systems design. International Journal of Control, 11: 771–778.
Spear, R.C. and Hornberger, G.M. (1978). Eutrophication in Peel Inlet: an analysis of behaviour and sensitivity of a poorly defined system. Report No. AS/R18, Centre for Resource and Environmental Studies, Australian National University, Canberra.
Sprott, D.A. (1977). Gauss’s Contributions to Statistics. Presented at the Gauss Bicentennial, Toronto. (D.A. Sprott is with the University of Waterloo, Ontario, Canada.)
Steele, L.P. (1981). Recursive Estimation in the Identification of Air Pollution Models. Ph.D. Thesis, Australian National University, Canberra.
Taylor, G.I. (1954). The dispersion of matter in turbulent flow through a pipe. Proceedings of the Royal Society, Series A, 223: 446–468.
Thissen, W. (1978). Investigations into the World 3 model: overall behaviour and policy conclusions. IEEE Transactions, Systems, Man, and Cybernetics, SMC-8: 172–182.
Whitehead, P.G. and Young, P.C. (1975). A dynamic-stochastic model for water quality in part of the Bedford Ouse river system. In G.C. Vansteenkiste (Editor), Computer Simulation of Water Resources Systems. North-Holland, Amsterdam, pp. 417–438.
Whitehead, P.G. and Young, P.C. (1979). Water quality in river systems — Monte Carlo analysis. Water Resources Research, 15: 451–459.
Whitehead, P.G., Young, P.C., and Hornberger, G.H. (1979). A systems model of streamflow and water quality in the Bedford-Ouse river, I: streamflow modelling. Water Research, 13:1155–1169.
Young, P.C. (1974). Recursive approaches to time series analysis. Bulletin of the Institute of Mathematics and its Application, 10: 209–224.
Young, P.C. (1976a). Some observations on instrumental variable methods of time series analysis. International Journal of Control, 23: 593–612.
Young, P.C. (1976b). Optimization in the presence of noise: a guided tour. In L.C.R. Dixon (Editor), Optimization in Action. Academic Press, London, pp. 517–573.
Young, P.C. (1977). A general theory of modeling for badly defined systems. Report No. AS/R9, Centre for Resource and Environmental Studies, Australian National University, Canberra. Also published in G.C. Vansteenkiste (Editor), Modeling, Identification, and Control in Environmental Systems. North-Holland, Amsterdam/American Elsevier, New York, pp. 103–135.
Young, P.C. (1980). Mining and the Natural Environment — Systems Analysis and Mathematical Modeling. In S.F. Harris (Editor), Social and Environmental Choice: The Impact of Uranium Mining in the Northern Territory. Centre for Resource and Environmental Studies, Australian National University, Canberra, pp. 64–78.
Young, P.C. (1981). Parameter estimation for continuous-time models — a survey. Automatica, 17: 23–29.
Young, P.C. (1982). An Introduction to Recursive Estimation. Lecture Notes Series, Springer, Berlin, in press.
Young, P.C. and Beck, M.B. (1974). The modeling and control of water quality in a river system. Automatica, 10:455–468.
Young, P.C. and Jakeman, A.J. (1979). Refined instrumental variable methods of recursive time series analysis, Part I: single input–single output systems. International Journal of Control, 29: 1–30.
Young, P.C. and Jakeman, A.J. (1980). Refined instrumental variable methods of recursive time series analysis, Part III: extensions. International Journal of Control, 31:741–764.
Young, P.C. and Kaldor, J.M. (1978). Recursive estimation: a methodological tool for investigating climatic change. Report No. AS/R14, Centre for Resource and Environmental Studies, Australian National University, Canberra (to be revised).
Young, P.C., Naughton, J.J., Neethling, C.G., and Shellswell, S.H. (1973). Macro-economic modeling: a case study. In P. Eykhoff (Editor), Identification and System Parameter Estimation. North-Holland, Amsterdam/American Elsevier, New York.
Young, P.C., Jakeman, A.J., and McMurtrie, R.E. (1980). An instrumental variable method for model structure identification. Automatica, 16: 281–294.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1983 International Institute for Applied Systems Analysis, Laxenburg/Austria
About this chapter
Cite this chapter
Young, P. (1983). The Validity and Credibility of Models for Badly Defined Systems. In: Beck, M.B., van Straten, G. (eds) Uncertainty and Forecasting of Water Quality. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-82054-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-82054-0_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-82056-4
Online ISBN: 978-3-642-82054-0
eBook Packages: Springer Book Archive