Search Results - "Votsi, I"

Confidence interval for the mean time to failure in semi-Markov models: an application to wind energy production by Votsi, I., Brouste, A.

“…Mean times to failure are fundamental indicators in reliability and related fields where stochastic processes are used to describe random, real-life systems…”
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Hidden Markov models revealing the stress field underlying the earthquake generation by Votsi, I., Limnios, N., Tsaklidis, G., Papadimitriou, E.

“…The application of the hidden Markov models (HMMs) is attempted for revealing key features for the earthquake generation which are not accessible to direct…”
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Hypotheses testing and posterior concentration rates for semi-Markov processes by Votsi, I., Gayraud, G., Barbu, V. S., Limnios, N.

“…In this paper, we adopt a nonparametric Bayesian approach and investigate the asymptotic behavior of the posterior distribution in continuous-time and general…”
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Estimation of the intensity of the hitting time for semi-Markov chains and hidden Markov renewal chains by Votsi, I., Limnios, N.

“…In this paper, we focus on a fundamental reliability measure, the discrete-time intensity of the hitting time (DTIHT), which is the discrete analogue of the…”
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Hidden Semi-Markov Modeling for the Estimation of Earthquake Occurrence Rates by Votsi, I., Limnios, N., Tsaklidis, G., Papadimitriou, E.

“…The present article aims at the description and application of a discrete-time hidden semi-Markov model in seismology in order to reveal some key features of…”
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Evaluation of malnutrition in hospitalised patients in Greece by Marakis, G., Karagiozoglou, T., Votsi, I., Kosteletou, E., Kontopoulou, L., Tsofliou, F.

“…Significant positive correlations were found between the total score of URS and percentage body weight loss (r 0.7, P<0.001) and between total score of…”
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Hypotheses testing and posterior concentration rates for semi-Markov processes by Barbu, V, Gayraud, Ghislaine, Limnios, N, Votsi, I

“…In this paper, we adopt a nonparametric Bayesian approach and investigate the asymptotic behavior of the posterior distribution in continuous time and general…”
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