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07Bib,Append_FungDSC - REFERENCES Abraham B(1981 Missing...

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163 REFERENCES Abraham, B. (1981). Missing Observations in Time Series. Communications in statistics Theory A , 10, 1643-1653. Beveridge, S. (1992). Least Squares Estimation of Missing Values in Time Series. Communications in statistics Theory A , 21(12), 3479-3496. Brockwell, P. J., & Davis, R. A. (1991). Time Series: Theory and Methods . New York, USA : Springer-Verlag. Chatfield, C. (2003). The Analysis of Time Series : An Introduction (6 th ed.) . New York, USA : John Wiley and Sons. Damsleth, E. (1979). Interpolating Missing Values in a Time Series. Scand J Statist ., 7, 33-39. Ferreiro, O. (1987). Methodologies for the Estimation of Missing Observations in Time Series. Statistics & Probability Letters , 5(1), 65-69. Gardner, G., Harvey, A. C., & Phillips, G. D. A. (1980). An Algorithm for Exact Maximum Likelihood Estimation of Autoregressive-Moving Average Models by Means of Kalman. Applied Statistics , 29, 311-322. Gerald, C. F., & Wheatley, P. O. (1994). Applied Numerical Analysis. Gomez, I. A., Burton, D. M., & Love, H. A. (1995). Imputing Missing Natural Resource Inventory Data and the Bootstrap. Natural Resource Modelling , 9(4), 299-328. Hamilton, J. D. (1994). Time Series Analysis . New Jersey, USA : Princeton University Press. Harvey, A. C. (2001). Forecasting, Structural Time Series Models and the Kalman Filter . Cambridge, UK : Cambridge University Press. Harvey, A. C., & Pierse, R.G. (1984). Estimating Missing Observations in Economic Time Series. Journal of the American Statistical Association , 79(385), 125-131. Janacek, G., & Swift, L. (1993). Time Series Forecasting Simulation & Application . West Sussex, England : Ellis Horwood Limited. Jones, R. H. (1980). Maximum Likelihood Fitting of ARMA Models to Time Series with Missing Observations. Technometrics , 22(3), 389-395. Kalman, R. E. (1960). A New Approach to Linear Filtering and Prediction Problems. Journal of Basic Energineering , 81, 35-45.
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164 Kohn, R., & Ansley, C. F. (1986). Estimation, Prediction, and Interpolation for ARIMA Models with Missing Data. Journal of the American Statistical Association , 81(395), 751-761. Ljung, G. M. (1989). A Note on the Estimation of Missing Values in Time Series. Communications in statistics simulation , 18(2), 459-465. Luceno, A. (1997). Estimation of Missing Values in Possibly Partially Nonstationary Vector Time Series. Biometrika , 84(2), 495-499 Nieto, F. H., & Martfncz, J. (1996). A Recursive Approach for Estimating Missing Observations in An Univariate Time Series. Communications in statistics Theory A , 25(9), 2101-2116. Pena, D., & Tiao, G. C. (1991). A Note on Likelihood Estimation of Missing Values in Time Series. The American statistician , 45(3), 212-213. Robinson, P. M. (1985). Testing for Serial Correlation in Regression with Missing Observations. Journal of the Royal Statistical Society B , 47, 429-437. Robinson, P. M., & Dunsmuir, W. (1981). Estimation of Time Series Models in the Presence of Missing Data. Journal of the American Statistical Association , 76(375), 560-568. Rosen, Y., & Porat, B. (1989). Optimal ARMA Parameter Estimation Based on The Sample Covariances for Data with Missing Observations. IEEE Transactions on Information Theorey , 35(2), 342-349.
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