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Autor
Shangodoyin D. K. (University of Botswana, Botswana), Ojo J. F. (University of Ibadan, Nigeria), Olaomi J. O. (University of Botswana, Botswana), Adebile A. O. (Federal Polytechnic, Ede)
Tytuł
Time Series Model for Predicting the Mean Death Rate of a Disease
Źródło
Statistics in Transition, 2012, vol. 13, nr 2, s. 405-418, aneks, bibliogr. 24 poz.
Słowa kluczowe
Analiza szeregów czasowych, Umieralność, Modele autoregresji
Time-series analysis, Mortality, Autoregression models
Uwagi
summ.
Abstrakt
This study develops a time series model to estimate the mean death rate of either an emerging disease or re-emerging disease with a bilinear induced model. The estimated death rate converges rapidly to the true parameter value for a given mean death at time t. The derived model could be used in predicting the m-step future death rate value of a given disease. We illustrated the new concept with real life data. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Biblioteka Główna Uniwersytetu Ekonomicznego w Poznaniu
Biblioteka Główna Uniwersytetu Ekonomicznego we Wrocławiu
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Bibliografia
Pokaż
  1. AKAIKE, H. (1973). Maximum Likelihood Identification of Gaussian Auto-regresssive Moving Average Models. Biometrika 60, 255-265.
  2. ALTMAN, K.L. (2003). The SARS epidemic. The front line research. New York Times. May 07 Edition.
  3. ANDERSON, T.W. (1971). The Statistical Analysis of Time Series, New York and London Wiley.
  4. BUCHWALD, P. (2007). A general bilinear model to describe growth or decline time profiles Math Biosci. 2007 205 (1): 108-36.
  5. BRUNI, C., DUPILLO, G. and KOCH, G. (1974). Bilinear Systems: An Appealing Class of Nearly Linear System in Theory and Application. IEEE Trans. Auto Control Ac-19, 334-338.
  6. CHEN, C.W.S. (1992). Bayesian Inferences and forecasting in bilinear time series models. Communications in Statistics - Theory and Methods 21(6), 17251743.
  7. DONNELLY, C.A., et. al (2003). Epidemiological determinants of spread of causal agent of severe acute respiratory syndrome in Hong Kong. The Lancet, 361,pg 1761-1766.
  8. GRANGER, C.W.J. and ANDERSON, A.P. (1978). Introduction to Bilinear Time Series Models. Vandenhoeck and Puprecht.
  9. GONCLAVES, E., JACOB P. and MENDES-LOPES N. (2000). A decision procedure for bilinear time series based on the Asymptotic Separation. Statistics, 333-348.
  10. HAGGAN, V. and OZAKI, T. (1980). Amplitude Dependent Exponential AR Model Fitting for Non-Linear Random Vibrations. Proc. International Time Series Meeting, Nottinghamm, ed. O. D. Anderson. North Holland.
  11. JONES, D.A. (1978). Non-linear Autoregressive Processes. Proc. Royal Soc. London (A) 360, 71-95.
  12. KINDIG, D A., SEPLAKI, C.L. and LIBBY, D.L. (2002). Death variation in US subpopulations. Bulletin of WHO, 80(1), pg 9-15.
  13. LI, W.K. and HUI, Y.V. (1983). Estimation of random coefficient autoregressive process: An empirical Bayes approach . Journal of Time Series Analysis, Vol. 4, No. 2. pg 89-94.
  14. LOHMANN, M.S. (2005). Data quality control and observations error estimation. www.ucar.edu.
  15. MARTINS, CM. (l997). A Note on the Third-Order Moment Structure of a bilinear model with Non-Independent Shocks. Potrugaliae Mathematica vol 56, 58-89.
  16. MATHERS, C D. and LONCAR, D. (2006). Projections of global mortality and burden of disease from 2002 to 2030. PLos Medicine. Vol. 3. Issue ll, pp 20ll-2030.
  17. MÖHLER, R.R. (l973). Bilinear Control Processes. New York: Academic Press.
  18. PRIESTELY, M B. (l978). Non-Linear Models in Time Series Analysis. The Statistician 27, l59-l76.
  19. SHANGODOYIN, D.K., OJO, J.F. and KOZAK, M. (20l0). Subsetting and identification of optimal models in one-dimensional bilinear time series modelling. International Journal of management science and Engineering management England, UK, 5(4), pp 252-260.
  20. SHANGODOYIN, D.K. (20l0). Using time series models to determine the death rate of a given disease. To appear in International Encyclopaedia of Statistical Science (Springer, USA).
  21. SUBBA RAO, T. (l98l). On the theory of Bilinear time Series Models ,Jour. R. Statist. Soc.B. 43, 244-255.
  22. TONG, H. AND CHAN, K. (2006). Estimating the death rate of an emerging disease by Time Series Analysis. Technical report, Department of Statistics & Actuarial Science, University of Iowa, Iowa, USA.
  23. TUAN DINH PHAM and LANH TAT TRAN (l98l). On the First Order Bilinear Time Series Model. Jour. Appli. Prob. l8, 6l7-627.
  24. WALKER, A.M. (l962). Large sample estimation of parameters of autoregressive processes with moving average residuals. Biometrika, 49, ll7-l3l.
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ISSN
1234-7655
Język
eng
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