Discussion of the Paper by Whittle

Abstract

Journal of the Royal Statistical Society: Series B (Methodological)Volume 53, Issue 3 p. 529-538 DiscussionFree Access Discussion of the Paper by Whittle First published: 1991 https://doi.org/10.1111/j.2517-6161.1991.tb01843.xAboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat REFERENCES IN THE DISCUSSION Akaike, H. (1980) Seasonal adjustment by a Bayesian modeling. J. Time Ser. Anal., 1, 1– 13. Bartlett, M. S. (1949) Some evolutionary stochastic processes. J. R. Statist. Soc. B, 11, 211– 229. Bartlett, M. S. (1961) Equations for stochastic path integrals. Proc. Camb. Phil. Soc., 57, 568– 573. Bartlett, M. S. (1981) Population and community structure and interaction. In The Mathematical Theory of the Dynamics of Biological Populations II (eds R. W. Hiorns and D. Cook), pp. 119– 137. New York: Academic Press. van den Bol, M. E. (1987) The analysis of a mixed model. Genstat Newslett., no. 20, 7– 12. Brotherton, T. and Gersch, W. (1981) A data analytic approach to the smoothing problem and some of its variations. In Proc. IEEE Conf. Decision and Control. San Diego: IEEE. Duncan, D. B. and Horn, S. D. (1972) Linear dynamic recursive estimation from the point of view of regression analysis. J. Am. Statist. Ass., 67, 815– 821. Hannan, E. J. and Deistler, M. (1988) The Statistical Theory of Linear Systems. New York: Wiley. Harvey, A. C. (1984) A unified view of statistical forecasting procedures. J. Forecast., 3, 245– 275. Harvey, A. C. (1989) Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge: Cambridge University Press. Henderson, C. R. (1953) Estimation of variance and covariance components. Biometrics, 9, 226– 252. Jakeman, A. J. and Young, P. C. (1984) Recursive filtering and the inversion of ill-posed causal problems. Util. Math., 25, 351– 376. de Jong, P. (1988) The likelihood for a state space model. Biometrika, 75, 165– 169. Kitagawa, G. (1981) Anon-stationary time-series model and its fitting by a recursive filter. J. Time Ser., 2, 103– 116. Kohn, R. and Ansley, C. F. (1986) Estimation, prediction and interpolation for ARIMA models with missing data. J. Am. Statist. Ass., 81, 751– 761. Kydland, F. E. and Prescott, E. C. (1990) Business cycles: real facts and a monetary myth. Q. Rev. Fed. Reserve Bank, Minneap., 14, 3– 18. Lukas, M. A. (1980) Regularisation. In The Application and Numerical Solution of Integral Equations (eds R. S. Anderrsen et al.). Sijthoff and Noordhoff. Ng, C. N. and Young, P. C. (1990) Recursive estimation and forecasting of nonstationary time-series. J. Forecast., 9, 173– 204. Reinsch, C. H. (1967) Smoothing by spline functions. Numer. Math., 10, 177– 183. Schiller, R. (1973) A distributed lag estimator derived from smoothness priors. Econometrica, 41, 775– 778. Simon, H. A. (1956) Dynamic programming under uncertainty with a quadratic criterion function. Econometrica, 24, 74– 81. Stigler, S. M. (1978) Mathematical statistics in the early states. Ann. Statist., 6, 239– 265. Theil, H. (1957) A note on certainty equivalence in economic planning. Econometrica, 25, 346– 349. West, M., Harrison, P. J. and Migon, H. S. (1985) Dynamic generalised linear models and Bayesian forecasting (with discussion). J. Am. Statist. Ass., 80, 73– 97. Whittaker, E. T. (1923) On a new method of graduation. Proc. Edinb. Math. Soc., 63– 75. Whittle, P. (1957) Curve and periodogram smoothing. J. R. Statist. Soc. B, 19, 38– 47. Whittle, P. (1963) Prediction and Regulation. London: English Universities Press. Whittle, P. (1983) Prediction and Regulation, 2nd edn. Oxford: Blackwell. Whittle, P. (1990) A risk-sensitive maximum principle. Syst. Control Lett., 15, 183– 192. Whittle, P. (1991) A risk-sensitive maximum principle; the case of imperfect state observation. IEEE Trans. Autotn. Control, to be published. Young, P. C. (1988) Recursive extrapolation, interpolation and smoothing of nonstationary time-series. In Identification and System Parameter Estimation (ed. H. F. Chen), pp. 33– 44. Oxford: Pergamon. Young, P. C. (1990) State space forecasting and seasonal adjustment. J. Forecast., 9, 2. Young, P. C. and Ng, C. N. (1989) Variance intervention. J. Forecast., 8, 399– 416. Young, P. C., Ng, C. N. and Armitage, P. (1989) A systems approach to economic forecasting and seasonal adjustment. Int. J. Comput. Math. Applic., 18, 481– 501. Volume53, Issue31991Pages 529-538 This article also appears in:Discussion Papers ReferencesRelatedInformation