1. Votsi, I., Gayraud, G., Barbu, V. & Limnios, N. (2021)

Hypotheses testing and posterior concentration rates for semi-Markov processes, Stat. Inference Stoch. Process, doi: 10.1007/s11203-021-09247-3.

 

2. Brouste, A.,  Soltane, M. & Votsi, I. (2020)

One-step estimation for the fractional Gaussian noise at high-frequency,  ESAIM: Probability and Statistics, 24,  827-841.

 

3. Votsi, I. (2019)

Conditional failure rates for semi-Markov chains, J Appl Stat, doi: 10.1080/02664763.2019.1610164.

 

4. Votsi, I. & Brouste, A. (2019)

 Confidence intervals for risk indicators in semi-Markov models: an application to wind energy production, J Appl Stat,  doi: 10.1080/02664763.2019.1566449.

 

 5. Koutroumpas, K., Ballarini, P., Votsi, I. & Cournède, P.-H. (2016)

 Bayesian parameter estimation for the Wnt pathway: An infinite mixture models approach, Bioinformatics, 32 (17), i781-i789. 

 

6. Hem,  S., Ly, S., Votsi, I. et al. (2016)

Estimating the burden of leptospirosis among febrile subjects aged below 20 years in Kampong Cham communities Cambodia, 2007-2009, PLoS One, 11(4): e0151555.

 

7. Votsi, I. & Limnios, N. (2015)

Estimation of the intensity of hitting time for semi-Markov chains and hidden Markov renewal chains, Journal of Nonparametric Statistics,  27 (2), 149-166.

 

8. Votsi, I., Limnios, N., Tsaklidis, G. & Papadimitriou, E. (2014)

Hidden semi-Markov modeling for the estimation of earthquake occurrence rates, Communications in Statistics: Theory and Methods, 43, 1484-1502.

 

9. Votsi, I., Limnios, N., Tsaklidis, G. & Papadimitriou, E. (2013)

Hidden Markov models revealing the stress field underlying the earthquake generation, Physica A: Statistical Mechanics and its Applications, 392, 2868-2885.

 

10. Votsi, I., Limnios, N., Tsaklidis, G. & Papadimitriou, E. (2012)

Estimation of the expected number of earthquake occurrences based on semi-Markov models, Methodology and Computing in Applied Probability, 14 (3), 685-703.

 

11. Votsi, I., Tsaklidis, G. & Papadimitriou, E. (2011)

Seismic hazard assessment in central Ionian islands area (Greece) based on stress release models, Acta Geophysica, 59 (4), 701-727.

1. Reliability indicators for semi-Markov models: the case of multiple trajectories, with A.Brouste.

 

2. One-step MLE for the autoregressive Markov switching model, with A.Brouste & F.Karamé.

 

3. Hypothesis testing for semi-Markov processes in a parametric context, with C.Farinetto.

 

Votsi, I., Limnios, N., Papadimitriou, E. & Tsaklidis, G. (2018)

Earthquake statistical analysis through multistate modeling, Mathematics and Statistics Series, Wiley-ISTE, ISBN: 978-1-119-57908-3, 180 p.

 

Votsi, I. (2018)

Reliability indicators for hidden Markov renewal models,  Reliability Engineering: Theory and Applications,  edited by Vonta, I. and Ram, M., Boca Raton: CRC Press.

 

Votsi, I. & Cournède, P.-H. (2016)

 A data augmentation scheme embedding a sequential Monte-Carlo method for bayesian parameter inference in state space models, 48èmes Journées de Statistique de la SFdS. 

 

Georgiadis, S., Limnios, N. & Votsi, I. (2013)

Reliability and probability of first occurred failure for discrete-time semi-Markov systems, Applied Reliability Engineering and Risk Analysis: Probabilistic Models and Statistical Inference, Wiley, DOI: 10.1002/9781118701881.ch12.