Trejo, L.J, Knuth K.,Prado R., Rosipal R., Kubitz K., Kochavi R., Matthews B., Zhang Y. (2007) EEG-based estimation of mental fatigue: Convergent evidence for a three-state model.  In D.D. Schmorrow, L.M. Reeves (Eds.): Augmented Cognition, HCII 2007, LNAI 4565, pp. 201\226211, New York: Springer.

Merl, D. and Prado (2007) Detecting selection in DNA sequences: Bayesian modeling and inference. In Proceedings of the Valencia/ISBA 8th World Meeting (eds. Bernardo J.M., Bayarri M.J., Berger J.O., Dawid A.P., Heckerman D., Smith A.F.M. and West M.), [with discussion].

Prado R., Merl D. and Escalante A.A. (2006) Assessing the effect of selection at the amino acid level in malaria antigen sequences via Bayesian generalized linear models. [Revised version of this article to appear in JASA].

Prado R., Molina F.J. and Huerta G. (2006) Multivariate Time Series Modeling and Classification via Hierarchical VAR Mixtures. Computational Statistics and Data Analysis, 51(3): 1445-1462.

Huerta G. and Prado R. (2006) Structured Priors for Multivariate Time Series. Journal of Statistical Planning and Inference, Vol 136, pp. 3802-3821.

Merl D., Prado R.and Escalante A. (2003) Bayesian Methods for Phylogeny Independent Detection of Positively Selected Amino Acid Sites 2003 Proceedings of the American Satistical Association, Section on Bayesian Statistical Science, Biopharmaceutical Section, ENAR [CD-ROM], Alexandria, VA: American Statistical Association.

Prado R. (2003) (pdf) Discussion of "Bayesian Harmonic Models for Musical Signal Analysis'' by Davy M. and Godsill S. J. In Bayesian Statistics VII (eds. Bernardo J.M., Bayarri M.J., Berger J.O., Dawid A.P., Heckerman D., Smith A.F.M. and West M.), Oxford University Press.

Huerta G. and Prado R. (2002), Exploring common structure in multiple time series via structured priors for autoregressive processes. A revised version of this report has been published in Estadistica (2005), vol57, p123-139 .

Prado R. and Huerta G. (2002) Time-varying autoregressions with model order uncertainty. Journal of Time Series Analysis, vol. 23(5) pp.599-618. Blackwell Publishers Ltd, Oxford, UK and Boston, USA.

Prado R. and García I. (2000) Analysis of electrocardiogram signals via wavelet based Bayesian models. CESMa Tech Report #00-14.

García I., Prado R. and Gomis P. (2000) Wavelet based Bayesian Models for characterizing Chagasic HRECG signals. CESMa Technical Report #00-11. In Computers in Cardiology, IEEE Computer Society Press.

Prado R., Huerta G. and West M. (2000) Bayesian time-varying autoregressions: Theory, methods and applications. Special issue on Time Series and Related Topics of "Resenhas", Journal of the Institute of Mathematics and Statistics of the University of Sao Paolo, 4, 405-422.

Prado R., West M. & Krystal A. (2001) Multi-channel EEG analyses via dynamic regression models with time-varying lag/lead structure. CESMa Technical Report #99-03 (ISDS Discussion Paper 99-05). Applied Statistics, 50, 95-109 .

West M., Prado R. & Krystal A. (1999). Evaluation and comparison of EEG traces: Latent Structure in Non-Stationary Time Series, Journal of the American Statistical Association, 94, 1083-1095.

Krystal A.D., Prado R. and West M. (1999) New methods of time series analysis for non-stationary EEG data: Eigenstructure decompositions of time varying autoregressions, Clinical Neurophysiology, 110: 2197-2206.

Krystal A.D., West M., Prado R., Greenside H., Zoldi S. and Weiner R.D.. (2000) The EEG Effects of ECT: Implications for rTMS, Depression and Anxiety 12 (3),157-165.

Krystal A.D.,Zoldi S., Prado R., Greenside H., Zoldi S. and West M. (1999) The spatiotemporal dynamics of generalized tonic-clonic seizure EEG data: Relevance to the clinical practice  of electroconvulsive therapy, In Nonlinear Dynamics and Brain Functioning (eds. N. Pradhan, P.E. Rapp and R. Sreenivasan), New York: Novascience.

Aguilar O., Huerta G., Prado R. & West M. (1999) Bayesian inference on latent structure in time series. In Bayesian Statistics 6 (eds: J.O. Berger et al), Oxford University Press.

Prado R. & West M.(1997). Exploratory modelling of multiple non-stationary time series: Latent process structure and decompositions.In Modelling Longitudinal and Spatially Correlated Data (ed: T. Gregoire), Springer-Verlag.

Prado R. (1998).Software for non-stationary time series analysis and decompositions via TVAR models, ISDS Working Paper #98-25.