Degradation analysis based on an extended inverse Gaussian process model with skew-normal random effects and measurement errors

•Extend traditional IG process by incorporating skew-normal random effects.•Derive analytically the lifetime distribution for the proposed EIG process model.•Develop MLEs of the model parameters for perfect and perturbed measurements.•Show the advantages of the proposed model through simulation and...

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Veröffentlicht in:	Reliability engineering & system safety Jg. 189; H. September; S. 261 - 270
Hauptverfasser:	Hao, Songhua, Yang, Jun, Berenguer, Christophe
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Barking Elsevier Ltd 01.09.2019 Elsevier BV Elsevier
Schlagworte:	Algorithms Applications Automatic Computer simulation Crack propagation Degradation Economic models Engineering Sciences Extended inverse Gaussian process model Extended MC integration algorithm Fatigue failure Fracture mechanics Gallium arsenide lasers Gaussian process Immunoglobulins Measurement errors Parameter estimation Reliability engineering Service life assessment Skew-normal random effects Statistics The MLE method Measurement errors The MLE method Extended inverse Gaussian process model Skew-normal random effects Extended MC integration algorithm the MLE method
ISSN:	0951-8320, 1879-0836
Online-Zugang:	Volltext
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