Bibliography

[Adenstedt 1974]

R. K. Adenstedt. On large-sample estimation for the mean of a stationary random sequence. Annals of Statistics, 2: 1095-1107, 1974.

[Aguilar et al. 1999]

Omar Aguilar, Gabriel Huerta, Raquel Prado, and Mike West. Bayesian inference on latent structure in time series. In José Miguel Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith, editors, Proceedings of the 6th International Meeting on Bayesian Statistics, Valencia, Spain. Oxford University Press, 1999.

[Aguilar and West 2000]

Omar Aguilar and Mike West. Bayesian dynamic factor models and portfolio allocation. Journal of Business & Economic Statistics, 18 (3): 338-357, 2000.

[Andrews 1993]

Donald W. K. Andrews. Tests for parameter instability and structural change with unknown change point. Econometrica, 61 (4): 821-856, July 1993.

[Bai 1997]

Jushan Bai. Estimation of a change point in multiple regression models. Review of Economics and Statistics, 79 (4): 551-562, 1997.

[Bai and Perron 1998]

Jushan Bai and Pierre Perron. Testing for and estimation of multiple structural changes. Econometrica, 66 (1): 47-79, 1998.

[Baillie 1996]

Richard T. Baillie. Long memory processes and fractional integration in econometrics. Journal of Econometrics, 73: 5-59, 1996.

[Baillie et al. 1996]

Richard T. Baillie, Ching-Fan Chung, and Margie A. Tieslau. Analysing inflation by the fractionally integrated ARFIMA-GARCH model. Journal of Applied Econometrics, 11: 23-40, 1996.

[Ball and Mankiw 1995]

Laurence Ball and N. Gregory Mankiw. Relative-price changes as aggregate supply shocks. Quarterly Journal of Economics, 110 (1): 161-193, 1995.

[Bansal 1997]

R. Bansal. An exploration of the forward premium puzzle in currency markets. Review of Financial Studies, 10: 369-403, 1997.

[Bansal and Dahlquist 2000]

R. Bansal and M. Dahlquist. The forward premium puzzle: Different tales from developed and emerging economies. Journal of International Economics, 51 (1): 115-144, 2000.

[Barberis 2000]

Nicholas Barberis. Investing for the long run when returns are predictable. Journal of Finance, 55: 225-264, 2000.

[Bauwens et al. 1999a]

Luc Bauwens, Charles S. Bos, and Herman K. Van Dijk. Adaptive polar sampling with an application to a Bayes measure of Value-at-Risk. Tinbergen Discussion Paper TI 99-082/4, Tinbergen Institute, 1999a.

[Bauwens et al. 2000]

Luc Bauwens, Charles S. Bos, and Herman K. Van Dijk. Adaptive polar sampling: A new MCMC method for ill-behaved posterior surfaces. In Wim Jansen and Jelke G. Bethlehem, editors, Proceedings in Computational Statistics 2000, pages 13-14. Statistics Netherlands, 2000.

[Bauwens and Lubrano 1998]

Luc Bauwens and Michel Lubrano. Bayesian inference on GARCH models using the Gibbs sampler. Econometrics Journal, pages C23-C46, 1998.

[Bauwens et al. 1999b]

Luc Bauwens, Michel Lubrano, and Jean-Fran Richard. Bayesian Inference in Dynamic Econometric Models. Advanced Texts in Econometrics. Oxford University Press, Oxford, 1999b.

[Bayes 1763]

Thomas Bayes. An essay towards solving a problem in the doctrine of chance. In Egon Sharpe Pearson and Maurice George Kendall, editors, Studies in the History of Statistics and Probablity. Griffen, London, 1763.

[Beran 1994]

Jan Beran. Statistics for Long-Memory Processes. Chapman & Hall, New York, 1994.

[Bollerslev 1986]

Tim Bollerslev. Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31 (3): 307-327, 1986.

[Bos et al. 1999]

Charles S. Bos, Philip Hans Franses, and Marius Ooms. Long memory and level shifts: Re-analyzing inflation rates. Empirical Economics, 24: 427-449, 1999.

[Bos et al. 2001]

Charles S. Bos, Philip Hans Franses, and Marius Ooms. Inflation, forecast intervals and long memory regression models. International Journal of Forecasting, 18, 2001.

[Bos et al. 2000a]

Charles S. Bos, Ronald J. Mahieu, and Herman K. Van Dijk. Daily exchange rate behaviour and hedging of currency risk. Journal of Applied Econometrics, 15 (6): 671-696, 2000a.

[Bos et al. 2000b]

Charles S. Bos, Ronald J. Mahieu, and Herman K. Van Dijk. On the variation of hedging decisions in daily currency risk management. In Bayesian Methods with Applications to Science, Policy, and Official Statistics, pages 31-40. International Society for Bayesian Analysis, 2000b.

[Bos 1969]

Pieter Cornelis Bos. The Functions of Money in Equilibrium and Disequilibrium. PhD thesis, Vrije Universiteit Amsterdam, 1969.

[Box and Jenkins 1970]

George E. P. Box and Gwilym M. Jenkins. Time Series Analysis, Forecasting and Control. Holden-Day, San Francisco, CA, 1970.

[Box et al. 1994]

George E. P. Box, Gwilym M. Jenkins, and G. C. Reinsel. Time Series Analysis, Forecasting and Control. Prentice Hall, Englewood Cliffs, NJ, 3rd edition, 1994.

[Breidt et al. 1998]

F. Jay Breidt, Nuno Crato, and Pedro de Lima. On the detection and estimation of long memory in stochastic volatility. Journal of Econometrics, 83 (1-2): 325-348, 1998.

[Brodsky and Hurvich 1999]

Julia Brodsky and Clifford M. Hurvich. Multi-step forecasting for long-memory processes. Journal of Forecasting, 18: 59-75, 1999.

[Carlin et al. 1992]

Bradley P. Carlin, Nicholas G. Polson, and David S. Stoffer. A Monte Carlo approach to nonnormal and nonlinear state-space modeling. Journal of the American Statistical Association, 87 (418): 493-500, June 1992.

[Carter and Kohn 1994]

C. K. Carter and R. Kohn. On Gibbs sampling for state space models. Biometrika, 81 (3): 541-553, 1994.

[Casella and George 1992]

G. Casella and E. George. Explaining the Gibbs sampler. The American Statistician, 46 (3): 167-174, August 1992.

[Chen and Schmeiser 1998]

Ming-Hui Chen and Bruce Schmeiser. Toward black-box sampling: A random-direction interior-point Markov chain approach. Journal of Computational & Graphical Statistics, 7 (1): 1-23, 1998.

[Cheung 1993]

Yin-Wong Cheung. Tests for fractional integration: A Monte Carlo investigation. Journal of Time Series Analysis, 14 (5): 331-345, 1993.

[Chib et al. 1998]

Siddharta Chib, Federico Nardari, and Neil Shephard. Markov chain Monte Carlo methods for generalized stochastic volatility models. Nuffield College working paper 1998-W21, University of Oxford, 1998.

[Chib et al. 2000]

Siddharta Chib, Federico Nardari, and Neil Shephard. Markov chain Monte Carlo methods for generalized stochastic volatility models. Unpublished manuscript, revision of , 2000.

[Chib 1995]

Siddhartha Chib. Marginal likelihood from the Gibbs output. Journal of the American Statistical Association, 90 (432): 1313-1321, 1995.

[Chib and Greenberg 1995]

Siddhartha Chib and Edward Greenberg. Understanding the Metropolis-Hastings algorithm. The American Statistician, 49 (4): 327-335, 1995.

[Chib and Greenberg 1996]

Siddhartha Chib and Edward Greenberg. Markov chain Monte Carlo simulation methods in econometrics. Econometric Theory, 12 (3): 409-431, 1996.

[Christoffersen 1998]

Peter F. Christoffersen. Evaluating interval forecasts. International Economic Review, 39 (4): 841-862, 1998.

[Courant 1954]

Richard Courant. Differential and Integral Calculus, volume II. Blackie, London, 2 edition, 1954.

[Davies and Harte 1987]

R. B. Davies and D. S. Harte. Tests for Hurst effect. Biometrika, 74: 95-102, 1987.

[De Jong 1989]

Piet De Jong. Smoothing and interpolation with the state-space model. Journal of the American Statistical Association, 84 (408): 1082-1088, December 1989.

[De Jong and Shephard 1995]

Piet De Jong and Neil Shephard. The simulation smoother for time series models. Biometrika, 82 (2): 339-350, 1995.

[Dickey 1971]

James Dickey. The weighted likelihood ratio, linear hypotheses on normal location parameters. Annals of Statistics, 42: 204-224, 1971.

[Doornik 1999]

Jurgen A. Doornik. Object-Oriented Matrix Programming using Ox. Timberlake Consultants Ltd, London, 3rd edition, 1999. See http://www.nuff.ox.ac.uk/Users/Doornik.

[Doornik and Hendry 2001]

Jurgen A. Doornik and David F. Hendry. Econometric Modelling using PcGive, volume III. London: Timberlake Consultants Ltd, 2001.

[Doornik and Ooms 1999]

Jurgen A. Doornik and Marius Ooms. A package for estimating, forecasting and simulating Arfima models: Arfima package 1.0 for Ox. Technical report, Nuffield College, Oxford, UK., 1999.

[Durbin and Koopman 2000]

J. Durbin and Siem Jan Koopman. Time series analysis of non-gaussian observations based on state space models from both classical and Bayesian perspectives. Journal of the Royal Statistical Society, Series B, 62 (1): 3-56, 2000.

[Engel and Hamilton 1990]

Charles Engel and James D. Hamilton. Long swings in the dollar: Are they in the data and do markets know it? American Economic Review, 4: 689-714, 1990.

[Engle 1982]

Robert F. Engle. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflations. Econometrica, 50: 987-1008, 1982.

[Engle 1995]

Robert F. Engle. ARCH: Selected Readings. Advanced Texts in Econometrics. Oxford: Oxford University Press, 1995.

[Evans and Lewis 1995]

Martin D. D. Evans and Karen K. Lewis. Do long-term swings in the dollar affect estimates of the risk premia? Review of Financial Studies, 8 (3): 709-742, 1995.

[Franses 1998]

Philip Hans Franses. Time Series Models for Business and Economic Forecasting. Cambridge University Press, 1998.

[Frühwirth-Schnatter 1994]

Sylvia Frühwirth-Schnatter. Data augmentation and dynamic linear models. Journal of Time Series Analysis, 15 (2): 183-202, 1994.

[Gali and Gertler 2000]

J. Gali and M. Gertler. Inflation dynamics: A structural econometric analysis. Technical Report 7551, National Bureau of Economic Research, 2000.

[Gelfand and Smith 1990]

Alan E. Gelfand and Adrian F. M. Smith. Sampling-based approaches to calculating marginal densities. Journal of the American Statistical Association, 85 (410): 398-409, June 1990.

[Geman and Geman 1984]

S. Geman and D. Geman. Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-6: 721-741, 1984.

[Geweke 1989]

John Geweke. Exact predictive densities for linear models with ARCH disturbances. Journal of Econometrics, 40: 63-86, 1989.

[Geweke 1992]

John Geweke. Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments. In José-Miguel Bernardo, J. O. Berger, A. P. Dawid, and Adrian F. M. Smith, editors, Bayesian Statistics 4: Proceedings of the Fourth Valencia International Meeting, pages 169-193. Oxford: Clarendon Press, 1992.

[Geweke 1999]

John Geweke. Using simulation methods for Bayesian econometric models: Inference, development, and communication. Econometric Reviews, 18 (1): 1-73, 1999.

[Geweke and Zhou 1996]

John Geweke and Guofu Zhou. Measuring the pricing error of the arbitrage pricing theory. Review of Financial Studies, 9 (2): 557-588, 1996.

[Gilks et al. 1996]

W. R. Gilks, S. Richardson, and D. J. Spiegelhalter, editors. Markov Chain Monte Carlo in Practice. Chapman & Hall, London, 1996.

[Gilks et al. 1994]

W. R. Gilks, G. O. Roberts, and E. I. George. Adaptive direction sampling. The Statistician, 43: 179-189, 1994.

[Gradshteyn and Ryzhik 1965]

I. S. Gradshteyn and I. M. Ryzhik. Tables of Integrals, Series and Products. Academic Press, London, 1965.

[Granger and Joyeux 1980]

Clive W. J. Granger and R. Joyeux. An introduction to long-memory time series models and fractional differencing. Journal of Time Series Analysis, 1: 15-29, 1980.

[Green 1995]

Peter J. Green. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika, 82: 711-732, 1995.

[Greene 1990]

William H. Greene. Econometric Analysis. Prentice Hall, New York, second edition, 1990.

[Hammersley and Handscomb 1964]

J. M. Hammersley and D. C. Handscomb. Monte Carlo Methods. Methuen & Co, London, 1964.

[Harvey 1989]

Andrew C. Harvey. Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press, Cambridge, 1989.

[Harvey et al. 1992]

Andrew C. Harvey, Esther Ruiz, and Enrique Sentana. Unobserved component time series with ARCH disturbances. Journal of Econometrics, 52: 129-157, 1992.

[Harvey et al. 1994]

Andrew C. Harvey, Esther Ruiz, and Neil Shephard. Multivariate stochastic variance models. Review of Economic Studies, 61: 247-264, 1994.

[Harvey et al. 1998]

David I. Harvey, Stephen J. Leybourne, and Paul Newbold. Tests for forecast encompassing. Journal of Business & Economic Statistics, 16: 254-259, 1998.

[Harvey and Newbold 2000]

David I. Harvey and Paul Newbold. Tests for multiple forecast encompassing. Journal of Applied Econometrics, 15 (5): 471-482, 2000.

[Hassler and Wolters 1995]

Uwe Hassler and Jürgen Wolters. Long memory in inflation rates: International evidence. Journal of Business & Economic Statistics, 13 (1): 37-46, 1995.

[Hastings 1970]

W. K. Hastings. Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57: 97-109, 1970.

[Hauser 1999]

Michael A. Hauser. Maximum likelihood estimators for ARMA and ARFIMA models: a Monte Carlo study. Journal of Statistical Planning and Inference, 80 (1-2): 229-256, 1999.

[Hidalgo and Robinson 1996]

Javier Hidalgo and Peter M. Robinson. Testing for structural change in a long-memory environment. Journal of Econometrics, 70 (1): 159-174, 1996.

[Hobert and Casella 1996]

James P. Hobert and George Casella. The effect of improper priors on Gibbs sampling in hierarchical linear mixed models. Journal of the American Statistical Association, 91 (436): 1461-1473, December 1996.

[Hooker 1999]

Mark A. Hooker. Are oil shocks inflationary? Asymmetric and nonlinear specifications versus changes in regime. Technical Report 1999-65, Federal Reserve Board, 1999.

[Hosking 1981]

J. R. M. Hosking. Fractional differencing. Biometrika, 68 (1): 165-176, 1981.

[Hsu 2000]

Chih-Chiang Hsu. Long memory or structural change: Testing method and empirical examination. Unpublished manuscript, 2000.

[Jacquier et al. 1994]

E. Jacquier, N. G. Polson, and P. E. Rossi. Bayesian analysis of stochastic volatility models. Journal of Business & Economic Statistics, 12: 371-417, 1994.

[Jorion 1985]

Philippe Jorion. International portfolio diversification with estimation risk. Journal of Business, 58 (3): 259-278, 1985.

[Jorion 1986]

Philippe Jorion. Bayes-Stein estimation for portfolio analysis. Journal of Financial and Quantitative Analysis, 21: 297-292, 1986.

[Jorion 1997]

Philippe Jorion. Value at Risk: The New Benchmark for Controlling Market Risk. New York: McGraw-Hill, 1997.

[JP Morgan 1997]

JP Morgan. RiskMetrics. Technical document, http://www.riskmetrics.com, 1997.

[Kandel et al. 1995]

S. Kandel, R. McCulloch, and R. Stambaugh. Bayesian inference and portfolio efficiency. Review of Financial Studies, 8: 1-53, 1995.

[Kass and Raftery 1995]

Robert E. Kass and Adrian E. Raftery. Bayes factors. Journal of the American Statistical Association, 90 (430): 773-795, 1995.

[Kass et al. 1990]

Robert E. Kass, Luke Tierney, and Adrian E. Raftery. The validity of posterior expansions based on Laplace's method. In Seymour Geisser, editor, Bayesian and Likelihood Methods in Statistics and Econometrics: Essays in Honor of George A. Barnard, pages 473-488. North Holland, Amsterdam, 1990.

[Kim et al. 1998]

Sangjoon Kim, Neil Shephard, and Siddhartha Chib. Stochastic volatility: Likelihood inference and comparison with ARCH models. Review of Economic Studies, 64: 361-393, 1998.

[Kleibergen and Van Dijk 1993]

Frank R. Kleibergen and Herman K. Van Dijk. Non-stationarity in GARCH models: A Bayesian analysis. Journal of Applied Econometrics, 8: S41-S61, 1993.

[Kloek and Van Dijk 1978]

Teun Kloek and Herman K. Van Dijk. Bayesian estimates of equation system parameters: An application of integration by Monte Carlo. Econometrica, 46: 1-20, 1978.

[Koop and Van Dijk 2000]

Gary Koop and Herman K. Van Dijk. Testing for integration using evolving trend and seasonal models: A Bayesian approach. Journal of Econometrics, 97 (2): 261-291, 2000.

[Koopman et al. 1999]

Siem Jan Koopman, Neil Shephard, and Jurgen A. Doornik. Statistical algorithms for models in state space using SsfPack 2.2. Econometrics Journal, 2: 107-160, 1999.

[Lamoureux and Lastrapes 1990]

C.G. Lamoureux and W.D. Lastrapes. Persistence-in-variance, structural change and the GARCH model. Journal of Business & Economic Statistics, 8: 225-234, 1990.

[LeBaron 1999]

Blake LeBaron. Technical trading rule profitability and foreign exchange intervention. Journal of International Economics, 49: 125-143, 1999.

[Liu and Sabatti 1998]

Jun S. Liu and Chiara Sabatti. Simulated sintering: Markov Chain Monte Carlo with spaces of varying dimensions. Proceedings of the 6th International Meeting on Bayesian Statistics, Valencia, Spain, 1998.

[Marinari and Parisi 1992]

Enzo Marinari and G. Parisi. Simulated tempering: A new Monte Carlo scheme. Europhysics Letters, 19 (6): 451-458, 1992.

[Mark 1995]

Nelson C. Mark. Exchange rates and fundamentals: Evidence on long-horizon predictability. American Economic Review, 85 (1): 201-218, 1995.

[McCulloch and Rossi 1990]

R. McCulloch and P. Rossi. Posterior, predictive, and utility-based approaches to testing the arbitrage pricing theory. Journal of Financial Economics, 28: 7-38, 1990.

[McCulloch and Rossi 1991]

R. McCulloch and P. Rossi. A Bayesian approach to testing the arbitrage pricing theory. Journal of Econometrics, 49: 141-168, 1991.

[McCulloch and Rossi 1992]

Robert E. McCulloch and P. Rossi. Bayes factors for nonlinear hypotheses and likelihood distributions. Biometrika, 79: 663-676, 1992.

[Metropolis et al. 1953]

N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, and E. Teller. Equations of state calculations by fast computing machines. Journal of Chemical Physics, 21: 1087-1091, 1953.

[Nelson and Plosser 1982]

Charles R. Nelson and Charles I. Plosser. Trends and random walks in macroeconomic time series; some evidence and implications. Journal of Monetary Economics, 10: 139-162, 1982.

[Nelson 1990]

D. B. Nelson. Stationarity and persistence in the GARCH(1, 1) model. Econometric Theory, 6: 318-334, 1990.

[Newey and West 1987]

Whitney K. Newey and Kenneth D. West. A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55: 703-708, 1987.

[Newton and Raftery 1994]

Michael A. Newton and Adrian E. Raftery. Approximate Bayesian inference by the weighted likelihood bootstrap. Journal of the Royal Statistical Society, Series B, 3: 3-48, 1994.

[Ooms 1996]

Marius Ooms. Long memory and seasonality in US consumer price inflation: An empirical investigation at varying levels of aggregation. Unpublished manuscript, December 1996.

[Ooms and Hassler 1997]

Marius Ooms and Uwe Hassler. On the effect of seasonal adjustment on the log-periodogram regression. Economics Letters, 56: 135-141, 1997.

[Perron 1989]

Pierre Perron. The great crash, the oil price shock, and the unit root hypothesis. Econometrica, 57 (6): 1361-1401, November 1989.

[Perron and Vogelsang 1992]

Pierre Perron and Timothy J. Vogelsang. Testing for a unit root in a time series with a changing mean: Corrections and extensions. Journal of Business & Economic Statistics, 10 (4): 467-469, 1992.

[Richardson and Green 1997]

Sylvia Richardson and Peter J. Green. On Bayesian analysis of mixtures with an unknown number of components. Journal of the Royal Statistical Society, Series B, 59 (4): 731-792, 1997.

[Ritter and Tanner 1992]

Christian Ritter and Martin A. Tanner. Facilitating the Gibbs sampler: The Gibbs stopper and the Griddy-Gibbs sampler. Journal of the American Statistical Association, 87 (419): 861-868, September 1992.

[Rubin 1987]

Donald B. Rubin. Comment: A noniterative sampling/importance resampling alternative to the data augmentation algorithm for creating a few imputations when fractions of missing information are modest: The SIR algorithm. Journal of the American Statistical Association, 82: 543-546, 1987.

[Satagopan and Newton 2000]

Jaya M. Satagopan and Michael A. Newton. Easy estimation of normalizing constants and Bayes factors from posterior simulation: Stabilizing the harmonic mean estimator. Unpublished manuscript, November 2000.

[Silverman 1986]

B. W. Silverman. Density Estimation for Statistics and Data Analysis. Chapman & Hall, New York, 1986.

[Smith and Roberts 1993]

A. F. M. Smith and G. O. Roberts. Bayesian computation via the Gibbs sampler and related Markov Chain Monte Carlo methods. Journal of the Royal Statistical Society, Series B, 55 (1): 3-24, 1993.

[Solnik 2000]

Bruno H. Solnik. International Investments. The Addison-Wesley Series in Finance. Addison-Wesley, Reading, Mass., 4th edition, 2000.

[Sowell 1992]

Fallaw Sowell. Maximum likelihood estimation of stationary univariate fractionally integrated time series models. Journal of Econometrics, 53: 165-188, 1992.

[Stock and Watson 1999]

James H. Stock and Mark W. Watson. Forecasting inflation. Journal of Monetary Economics, 44: 293-335, 1999.

[Tanner and Wong 1987]

Martin A. Tanner and Wing Hung Wong. The calculation of posterior distributions by data augmentation. Journal of the American Statistical Association, 82: 528-550, 1987.

[Taylor 1994]

Stephen J. Taylor. Modeling stochastic volatility: A review and comparative study. Mathematical Finance, 4 (2): 183-204, 1994.

[Tierney 1994]

Luke Tierney. Markov chains for exploring posterior distributions. Annals of Statistics, 22: 1701-1762, 1994.

[Van Dijk 1999]

Dick J. C. Van Dijk. Smooth Transition Models: Extensions and Outlier Robust Inference. PhD thesis, Tinbergen Institute, Erasmus University Rotterdam, September 1999. TI 200.

[Van Dijk and Kloek 1980]

Herman K. Van Dijk and Teun Kloek. Further experience in Bayesian analysis using Monte Carlo integration. Journal of Econometrics, 14: 307-328, 1980.

[Van Dijk et al. 1985]

Herman K. Van Dijk, Teun Kloek, and C. Guus E. Boender. Posterior moments computed by mixed integration. Journal of Econometrics, 29: 3-18, 1985.

[Verdinelli and Wasserman 1995]

Isabella Verdinelli and Larry Wasserman. Computing Bayes factors using a generalization of the Savage-Dickey density ratio. Journal of the American Statistical Association, 90 (430): 614-618, 1995.

[West 2001]

K. D. West. Tests for forecast encompassing when forecasts depend on estimated regression parameters. Journal of Business & Economic Statistics, 19: 29-33, 2001.

[West et al. 1985]

Mike West, P. Jeff Harrison, and Helio S. Migon. Dynamic generalized linear models and Bayesian forecasting. Journal of the American Statistical Association, 80 (389): 73-98, March 1985.

[Yu and Mykland 1998]

Bin Yu and Per Mykland. Looking at Markov samplers through cusum path plots: A simple diagnostic idea. Statistics and Computing, 8 (3): 275-286, 1998.

[Zeger and Karim 1991]

Scott L. Zeger and M. Rezaul Karim. Generalized linear models with random effects: A Gibbs sampling approach. Journal of the American Statistical Association, 86: 79-86, 1991.

[Main page] [Top] [Next: Summary in Dutch]
Last change: 9/12/2001