Standard Article

You have free access to this content

Forecasting, Environmental

Stochastic Modeling and Environmental Change

  1. Peter C. Young1,2,
  2. Diego J. Pedregal3

Published Online: 15 SEP 2006

DOI: 10.1002/9780470057339.vaf007

Encyclopedia of Environmetrics

Encyclopedia of Environmetrics

How to Cite

Young, P. C. and Pedregal, D. J. 2006. Forecasting, Environmental. Encyclopedia of Environmetrics. 3.

Author Information

  1. 1

    Lancaster University, UK

  2. 2

    Australian National University College of Medicine, Biology & Environment, Canberra, Australia

  3. 3

    Universidad de Castilla la Mancha, spain

Publication History

  1. Published Online: 15 SEP 2006

References

  1. References
  • 1
    Young, P.C. (1998). Data-based mechanistic modelling of environmental, ecological, economic and engineering systems, Environmental Modelling and Software 13, 105122.
  • 2
    Holt, C.C. (1957). Forecasting seasonals and trends by exponentially weighted moving averages, ONR Research Memorandum 52, Pittsburgh, Carnegie Institute of Technology.
  • 3
    Winters, P.R. (1960). Forecasting sales by exponentially weighted moving averages, Management Science 6, 324342.
  • 4
    Harvey, A.C. (1989). Forecasting Structural Time-series Models and the Kalman Filter, Cambridge University Press, Cambridge.
  • 5
    Box, G.E.P. & Jenkins, G.M. (1970, 1976). Time-series Analysis: Forecasting and Control, Holden-Day, San Francisco.
  • 6
    Abraham, B. & Ledolter, J. (1983). Statistical Methods for Forecasting, New York, Wiley.
  • 7
    Chatfield, C. (1984). The Analysis of Time-series: An Introduction, Chapman & Hall, London.
  • 8
    Diebold, F. (1998). Elements of Forecasting, South-Western, Cincinnati.
  • 9
    Diggle, P.J. (1990). Time-series: A Biostatistical Introduction, Clarendon Press, Oxford.
  • 10
    Granger, C.W.J. & Newbold, P. (1986). Forecasting Economic Time-series, 2nd Edition, Academic Press, San Diego.
  • 11
    Harvey, A.C. (1981). Time-series Models, Philip Allan, New York.
  • 12
    Baillie, R.T. (1996). Long memory processes and fractional integration in econometrics, Journal of Econometrics 73, 559.
  • 13
    Quenouille, M.H. (1957). The Analysis of Multiple Time-series, Griffin, London.
  • 14
    Tiao, G.C. & Box, G.E.P. (1981). Modelling multiple time-series with applications, Journal of the American Statistical Association 76, 802816.
  • 15
    Lütkepohl, H. (1991). Introduction to Multiple Time-series Analysis, Springer-Verlag, Berlin.
  • 16
    Harrison, P.J. & Stevens, C.F. (1976). Bayesian forecasting, Journal of the Royal Statistical Society, Series B 38, 205247.
  • 17
    Jakeman, A.J. & Young, P.C. (1984). Recursive filtering and the inversion of ill-posed causal problems, Utilitas Mathematica 35, 351376.
  • 18
    Koopman, S.J., Harvey, A.C., Doornik, J.A. & Shephard, N. (1995). STAMP 5.0: Structural Time-series Analyser Modeller and Predictor, Timberlake Consultants.
  • 19
    Ng, C.N. & Young, P.C. (1990). Recursive estimation and forecasting of nonstationary time-series, Journal of Forecasting 9, 173204.
  • 20
    Pole, A., West, M. & Harrison, J. (1995). Applied Bayesian Forecasting and Time-series Analysis, Chapman & Hall, New York.
  • 21
    West, M. & Harrison, J. (1989). Bayesian Forecasting and Dynamic Models, Springer-Verlag, New York.
  • 22
    Young, P.C. (1984). Recursive Estimation and Time-series Analysis, Springer-Verlag, Berlin.
  • 23
    Young, P.C. (1994). Time-variable parameter and trend estimation in nonstationary economic time-series, Journal of Forecasting 13, 179210.
  • 24
    Young, P.C., Ng, C.N. & Armitage, P. (1989). A systems approach to economic forecasting and seasonal adjustment, International Journal on Computers and Mathematics with Applications, Special Issue on System Theoretic Methods in Economic Modelling 18, 481501.
  • 25
    Young, P.C., Pedregal, D.J. & Tych, W. (1999). Dynamic harmonic regression, Journal of Forecasting 18, 369394.
  • 26
    Burman, J.P. (1980). Seasonal adjustment by signal extraction, Journal of the Royal Statistical Society, Series A 143, 321337.
  • 27
    Hillmer, S.C., Bell, W.R. & Tiao, G.C. (1983). Modelling considerations in the seasonal adjustment of economic time-series, in Applied Time-series Analysis of Economic Data, A. Zellner, ed., US Dept. of Commerce Bureau of the Census, Washington, pp. 74100.
  • 28
    Maravall, A. & Gómez, V. (1998). Programs TRAMO and SEATS, Instructions for the User (Beta Version: June 1998), Madrid, Bank of Spain.
  • 29
    Ljung, L. & Söderstrom, T. (1983). Theory and Practice of Recursive Estimation, MIT Press, Cambridge.
  • 30
    Kalman, R.E. (1960). A new approach to linear filtering and prediction problems, Journal of Basic Engineering 83-D, 95108.
  • 31
    Tych, W., Pedregal, D.J., Young, P.C. & Davies, J. (2001). Multi-rate forecasting of telephone call demand: a software package for unobserved components modelling and forecasting, International Journal of Forecasting, in press.
  • 32
    Young, P.C. & Pedregal, D.J. (1997). Modulated cycles; a new approach to modelling seasonal/cyclical behaviour in unobserved components models, Centre for Research on Environmental Systems and Statistics (CRES), Technical Note No. TR/145.
  • 33
    Young, P.C. & Tomlin, C. (2000). Data-based mechanistic modelling and adaptive flow forecasting, in Flood Forecasting: what does Current Research Offer the Practitioner? M. Lees & P. Walsh, eds, British Hydrological Society, Occasional Paper No. 12, produced by the Centre for Ecology & Hydrology on behalf of the British Hydrological Society, pp. 2640.
  • 34
    Engle, R.F. & Granger, C.W.J. (1987). Cointegration and error correction: representation, estimation & testing, Econometrica 55, 251276.
  • 35
    Harvey, A.C. & Koopman, S.J. (1997). Comments on multivariate structural time-series Models, in System Dynamics in Economic and Financial Models, C. Heij, H. Schumacher, B. Hanzon & K. Praagman, eds, Wiley, Chichester.
  • 36
    Bryson, A.E. & Ho, Y.C. (1969). Applied Optimal Control, Optimization, Estimation and Control, Blaisdell, Waltham.
  • 37
    Young, P.C. & Ng, C.N. (1989). Variance intervention, Journal of Forecasting 8, 399416.
  • 38
    Young, P.C. & Pedregal, D.J. (1999). Recursive and en-block approaches to signal extraction, Journal of Applied Statistics 26, 103128.
  • 39
    Schweppe, F. (1965). Evaluation of likelihood function for Gaussian signals, IEEE Transactions on Information Theory 11, 6170.
  • 40
    Dempster, A.P., Laird, N.M. & Rubin, D.B. (1977). Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, Series B 39, 138.
  • 41
    Young, P.C. (1999). Nonstationary time-series analysis and forecasting, Progress in Environmental Science 1, 348.
  • 42
    Young, P.C. (2000). The Mauna Loa atmospheric CO2 data: new analysis and forecasting results, Centre for Research on Environmental Systems and Statistics (CRES), Technical Note No. TR/180.
  • 43
    Young, P.C., Ng, C.N., Lane, K. & Parker, D. (1991). Recursive forecasting, smoothing and seasonal adjustment of nonstationary environmental data, Journal of Forecasting 10, 5789.
  • 44
    Young, P.C. (1993). Time variable and state dependent modelling of nonstationary and nonlinear systems, in Developments in Time Series Analysis, T. Subba-Rao, ed., Chapman & Hall, London.
  • 45
    Young, P.C. (2001). Data-based mechanistic modelling and validation of rainfall-flow processes, in Model Validation in Hydrological Science, M.G. Anderson, ed., Wiley, Chichester, pp. 117162.
  • 46
    Young, P.C. (2000). Stochastic, dynamic modelling and signal processing: time variable and state-dependent parameter estimation, in Nonstationary and Non- linear Signal Processing, W.J. Fitzgerald, A. Walden, R. Smith & P.C. Young, eds, Cambridge University Press, Cambridge, pp. 74114.
  • 47
    Young, P.C. (2001). The identification and estimation of nonlinear stochastic systems, in Nonlinear Dynamics and Statistics, A.I. Mees, ed., Birkhäuser, Boston, in press.
  • 48
    Young, P.C. & Beven, K.J. (1994). Data-based mechanistic modelling and the rainfall-flow nonlinearity, Environmetrics 5, 335363.
  • 49
    Lees, M., Young, P.C., Beven, K.J., Ferguson, S. & Burns, J. (1994). An adaptive flood warning system for the River Nith at Dumfries, in River Flood Hydraulics, W.R. White & J. Watts, eds, Institute of Hydrology, Wallingford.
  • 50
    Young, P.C. (1992). Parallel processes in hydrology and water quality, Journal of the Institute of Water and Environmental Management 6, 598612.