Confidence intervals for risk indicators in semi-Markov models: an application to wind energy production

Irene Votsi (1) , Alexandre Brouste (1)

1 LMM - Laboratoire Manceau de Mathématiques

Mean times to failure are fundamental indicators in reliability and related fields. Here we focus on the conditional mean time to failure defined in a semi-Markov context. A discrete time semi-Markov model with discrete state space is employed, which allows for realistic description of systems under risk. Our main objective is to estimate the conditional mean time to failure and provide asymptotic properties of its nonparametric estimator. Consistency and asymptotic normality results are provided. Our methodology is tested in a real wind dataset and indicators associated with the wind energy production are estimated.

Mots clés: Risk indicators; semi-Markov systems; empirical estimators; asymptotic properties; wind data

Domaines: Statistiques [math.ST]

Irene Votsi, Alexandre Brouste. Confidence intervals for risk indicators in semi-Markov models: an application to wind energy production. Journal of Applied Statistics, 2019, 46 (10), pp.1756-1773. ⟨10.1080/02664763.2019.1566449⟩. ⟨hal-01590520⟩