[1]E. Anderson, Z. Bai, C. Bischof, S. Blackford, J. Demmel, J. Dongarra, J. Du Croz, A. Greenbaum, S. Hammarling, A. McKenney, and D. Sorensen. LAPACK Users’ Guide. Society for Industrial and Applied Mathematics, Philadelphia, PA, third edition, 1999.
[2]Craig F. Ansley and Robert Kohn. A note on reparameterizing a vector autoregressive moving average model to enforce stationarity. Journal of Statistical Computation and Simulation, pages 99–106, June 1986.
[3]Stefan Behnel, Robert Bradshaw, Craig Citro, Lisandro Dalcin, Dag Sverre Seljebotn, and Kurt Smith. Cython: The Best of Both Worlds. Computing in Science & Engineering, pages 31–39, March 2011.
[4]Olivier Jean Blanchard and Charles M. Kahn. The Solution of Linear Difference Models under Rational Expectations. Econometrica, pages 1305–1311, July 1980.
[5]C. K. Carter and R. Kohn. On Gibbs sampling for state space models. Biometrika, pages 541–553, September 1994.
[6]Siddhartha Chib and Edward Greenberg. Understanding the Metropolis-Hastings Algorithm. The American Statistician, pages 327–335, November 1995.
[7]Jacques J. F. Commandeur, Siem Jan Koopman, and Marius Ooms. Statistical Software for State Space Methods. Journal of Statistical Software, pages 1–18, 2011.
[8]David N. DeJong and Chetan Dave. Structural Macroeconometrics: (Second Edition). Princeton University Press, October 2011.
[9]J. Durbin and S. J. Koopman. A simple and efficient simulation smoother for state space time series analysis. Biometrika, pages 603–616, August 2002.
[10]James Durbin and Siem Jan Koopman. Time Series Analysis by State Space Methods: Second Edition. Oxford University Press, May 2012.
[11]Mohinder Grewal and Angus Andrews. Kalman Filtering: Theory and Practice with MATLAB. Wiley-IEEE Press, Hoboken, New Jersey, 4 edition edition, December 2014.
[12]James Douglas Hamilton. Time Series Analysis. Princeton University Press, January 1994.
[13]Eric Jones, Travis Oliphant, and Pearu Peterson. SciPy: Open source scientific tools for Python. 2001.
[14]Borus Jungbacker and Siem Jan Koopman. Likelihood-based dynamic factor analysis for measurement and forecasting. The Econometrics Journal, pages n/a–n/a, June 2014.
[15]R. E. Kalman. A New Approach to Linear Filtering and Prediction Problems. Journal of Basic Engineering, pages 35–45, March 1960.
[16]Chang-Jin Kim and Charles R. Nelson. State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications. MIT Press Books, The MIT Press, 1999.
[17]Paul Klein. Using the generalized Schur form to solve a multivariate linear rational expectations model. Journal of Economic Dynamics and Control, pages 1405–1423, September 2000.
[18]Gary Koop. Bayesian Econometrics. Wiley-Interscience, Chichester ; Hoboken, N.J, 1 edition edition, July 2003.
[19]S. J. Koopman and J. Durbin. Fast Filtering and Smoothing for Multivariate State Space Models. Journal of Time Series Analysis, pages 281–296, May 2000.
[20]S.j. Koopman and J. Durbin. Filtering and smoothing of state vector for diffuse state–space models. Journal of Time Series Analysis, pages 85–98, January 2003.
[21]Siem Jan Koopman. Disturbance Smoother for State Space Models. Biometrika, pages 117–126, March 1993.
[22]B. D. McCullough and H. D. Vinod. The Numerical Reliability of Econometric Software. Journal of Economic Literature, pages 633–665, June 1999.
[23]Roy Mendelssohn. The STAMP Software for State Space Models. Journal of Statistical Software, pages 1–18, 2011.
[24]John F. Monahan. A note on enforcing stationarity in autoregressive-moving average models. Biometrika, pages 403–404, August 1984.
[25]M. Morf and T. Kailath. Square-root algorithms for least-squares estimation. IEEE Transactions on Automatic Control, pages 487–497, August 1975.
[26]Anand Patil, David Huard, and Christopher J. Fonnesbeck. PyMC: Bayesian Stochastic Modelling in Python. Journal of Statistical Software, pages 1–81, 2010.
[27]Francisco J. Ruge-Murcia. Methods to estimate dynamic stochastic general equilibrium models. Journal of Economic Dynamics and Control, pages 2599–2636, August 2007.
[28]Skipper Seabold and Josef Perktold. Statsmodels: Econometric and Statistical Modeling with Python. In Proceedings of the 9th Python in Science Conference, 57–61. 2010.
[29]Christopher A. Sims. Solving Linear Rational Expectations Models. Computational Economics, pages 1–20, October 2002.
[30]Frank Smets and Rafael Wouters. Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach. The American Economic Review, pages 586–606, June 2007.
[31]Christopher Strickland, Robert Burdett, Kerrie Mengersen, and Robert Denham. PySSM: A Python Module for Bayesian Inference of Linear Gaussian State Space Models. Journal of Statistical Software, pages ??–??, 2014.
[32]Luke Tierney. Markov Chains for Exploring Posterior Distributions. The Annals of Statistics, pages 1701–1728, December 1994.
[33]Peter Wegner. Concepts and Paradigms of Object-oriented Programming. SIGPLAN OOPS Mess., pages 7–87, August 1990.
[34]Mike West and Jeff Harrison. Bayesian Forecasting and Dynamic Models. Springer, New York, 2nd edition edition, March 1999.