The SSM Procedure

Akaike, H. (1974), “A New Look at the Statistical Model Identification,” IEEE Transactions on Automatic Control, AC-19, 716–723.

Anderson, B. D. and Moore, J. B. (1979), Optimal Filtering, Englewood Cliffs, NJ: Prentice-Hall.

Ansley, C. and de Jong, P. (2012), “Inferring and Predicting Global Temperature Trends,” Slide presentation at "Time Series Econometrics: Conference in Honour of Andrew Harvey.
URL http://www.oxford-man.ox.ac.uk/sites/default/files/events/Piet%20de%20Jong.pdf

Baltagi, B. H. (1995), Econometric Analysis of Panel Data, New York: John Wiley & Sons.

Baltagi, B. H. and Levin, D. (1992), “Cigarette Taxation: Raising Revenues and Reducing Consumption,” Structural Change and Economic Dynamics, 3, 321–335.

Bell, W. R. (2011), “REGCMPNT—a Fortran Program for Regression Models with ARIMA Component Errors,” Journal of Statistical Software, 41, 1–23.
URL http://www.jstatsoft.org/v41/i07/

Box, G. E. P. and Jenkins, G. M. (1976), Time Series Analysis: Forecasting and Control, Rev. Edition, San Francisco: Holden-Day.

Bozdogan, H. (1987), “Model Selection and Akaike’s Information Criterion (AIC): The General Theory and Its Analytical Extensions,” Psychometrika, 52, 345–370.

Burnham, K. P. and Anderson, D. R. (1998), Model Selection and Inference: A Practical Information-Theoretic Approach, New York: Springer-Verlag.

de Jong, P. (1989), “Smoothing and Interpolation with the State-Space Model,” Journal of the American Statistical Association, 84, 1085–1088.

de Jong, P. (1991), “The Diffuse Kalman Filter,” Annals of Statistics, 19, 1073–1083.

de Jong, P. and Chu-Chun-Lin, S. (2003), “Smoothing with an Unknown Initial Condition,” Journal of Time Series Analysis, 24, 141–148.

de Jong, P. and Mazzi, S. (2001), “Modeling and Smoothing Unequally Spaced Sequence Data,” Statistical Inference for Stochastic Processes, 4, 53–71.

de Jong, P. and Penzer, J. (1998), “Diagnosing Shocks in Time Series,” Journal of the American Statistical Association, 93, 796–806.

Diggle, P. J., Liang, K.-Y., and Zeger, S. L. (1994), Analysis of Longitudinal Data, Oxford: Clarendon Press.

Durbin, J. and Koopman, S. J. (2001), Time Series Analysis by State Space Methods, Oxford: Oxford University Press.

Eubank, R. L., Huang, C., and Wang, S. (2003), “Adaptive Order Selection for Spline Smoothing,” Journal of Computational and Graphical Statistics, 12, 382–397.

Givens, G. H. and Hoeting, J. A. (2005), Computational Statistics, Hoboken, NJ: John Wiley & Sons.

Hannan, E. J. and Quinn, B. G. (1979), “The Determination of the Order of an Autoregression,” Journal of the Royal Statistical Society, Series B, 41, 190–195.

Harvey, A. C. (1989), Forecasting, Structural Time Series Models, and the Kalman Filter, Cambridge: Cambridge University Press.

Hurvich, C. M. and Tsai, C.-L. (1989), “Regression and Time Series Model Selection in Small Samples,” Biometrika, 76, 297–307.

Jones, R. H. (1980), “Maximum Likelihood Fitting of ARMA Models to Time Series with Missing Observations,” Technometrics, 22, 389–396.

Jones, R. H. (1993), Longitudinal Data with Serial Correlation: A State Space Approach, London: Chapman & Hall.

Kohn, R., Ansley, C., and Tharm, D. (1991), “The Performance of Cross-Validation and Maximum Likelihood Estimators of Spline Smoothing Parameters,” Journal of the American Statistical Association, 86, 1042–1050.

Kohn, R. and Ansley, C. F. (1991), “A Signal Extraction Approach to the Estimation of Treatment and Control Curves,” Journal of the American Statistical Association, 86, 1034–1041.

Koopman, S. J., Mallee, M. I. P., and van der Wel, M. (2010), “Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson-Siegel Model with Time-Varying Parameters,” Journal of Business and Economic Statistics, 28, 329–343.

Nelson, C. R. and Siegel, A. F. (1987), “Parsimonious Modeling of Yield Curves,” Journal of Business, 60, 473–489.

Reinsel, G. C. (1997), Elements of Multivariate Time Series Analysis, 2nd Edition, New York: Springer-Verlag.

Schwarz, G. (1978), “Estimating the Dimension of a Model,” Annals of Statistics, 6, 461–464.

Selukar, R. S. (2010), “Estimability of the Linear Effects in State Space Models with an Unknown Initial Condition,” Journal of Time Series Analysis, 31, 167–168.

Wecker, W. E. and Ansley, C. F. (1983), “The Signal Extraction Approach to Nonlinear Regression and Spline Smoothing,” Journal of the American Statistical Association, 78, 81–89.