On Semi-Markov Modelling and Inference for Multi-State Systems

被引：2
|
作者：
Barbu, Vlad Stefan [1 ]
Karagrigoriou, Alex [2 ]
Makrides, Andreas [3 ]
机构：
[1] Univ Rouen, Lab Math Raphael Salem, St Etienne, France
[2] Univ Aegean, Dept Math, Samos, Greece
[3] Univ Cyprus, Dept Math & Stat, Nicosia, Cyprus
来源：
2016 SECOND INTERNATIONAL SYMPOSIUM ON STOCHASTIC MODELS IN RELIABILITY ENGINEERING, LIFE SCIENCE AND OPERATIONS MANAGEMENT (SMRLO) | 2016年
关键词：
multi-state system; reliability theory; survival analysis; reliability indicators; semi-Markov processes; parameter estimation;
D O I：
10.1109/SMRLO.2016.20
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this work we focus on multi state systems that we model by means of semi-Markov processes. The sojourn times are seen to be independent not identically distributed random variables and assumed to belong to a general class of distributions that includes several popular reliability distributions like the exponential, Weibull, and Pareto. We obtain maximum likelihood estimators of the parameters of interest and for various quantities related to the system under study.
引用
收藏
页码：56 / 60
页数：5
相关论文
共 50 条
  • [31] Inference for transition probabilities in non-Markov multi-state models
    Per Kragh Andersen
    Eva Nina Sparre Wandall
    Maja Pohar Perme
    Lifetime Data Analysis, 2022, 28 : 585 - 604
  • [32] Combining Markov and Semi-Markov Modelling for Assessing Availability and Cybersecurity of Cloud and IoT Systems
    Kharchenko, Vyacheslav
    Ponochovnyi, Yuriy
    Ivanchenko, Oleg
    Fesenko, Herman
    Illiashenko, Oleg
    CRYPTOGRAPHY, 2022, 6 (03)
  • [33] Evaluating the effect of healthcare providers on the clinical path of heart failure patients through a semi-Markov, multi-state model
    Gasperoni, Francesca
    Ieva, Francesca
    Paganoni, Anna Maria
    Jackson, Christopher H.
    Sharples, Linda
    BMC HEALTH SERVICES RESEARCH, 2020, 20 (01)
  • [34] Inference for transition probabilities in non-Markov multi-state models
    Andersen, Per Kragh
    Wandall, Eva Nina Sparre
    Perme, Maja Pohar
    LIFETIME DATA ANALYSIS, 2022, 28 (04) : 585 - 604
  • [35] Evaluating the effect of healthcare providers on the clinical path of heart failure patients through a semi-Markov, multi-state model
    Francesca Gasperoni
    Francesca Ieva
    Anna Maria Paganoni
    Christopher H Jackson
    Linda Sharples
    BMC Health Services Research, 20
  • [36] STATISTICAL INFERENCE AND UNCERTAINTY ASSESSMENT FOR MULTI-STATE SYSTEMS
    Fiondella, Lance
    INTERNATIONAL JOURNAL OF RELIABILITY QUALITY AND SAFETY ENGINEERING, 2009, 16 (05) : 453 - 467
  • [37] Scalable Bayesian Inference for Coupled Hidden Markov and Semi-Markov Models
    Touloupou, Panayiota
    Finkenstadt, Barbel
    Spencer, Simon E. F.
    JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2020, 29 (02) : 238 - 249
  • [38] A Spectral Algorithm for Inference in Hidden semi-Markov Models
    Melnyk, Igor
    Banerjee, Arindam
    ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 38, 2015, 38 : 690 - 698
  • [39] Structured Inference for Recurrent Hidden Semi-Markov Model
    Liu, Hao
    He, Lirong
    Bai, Haoli
    Dai, Bo
    Bai, Kun
    Xu, Zenglin
    PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2018, : 2447 - 2453
  • [40] A semi-Markov approach for modelling asset deterioration
    Black, M
    Brint, AT
    Brailsford, JR
    JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2005, 56 (11) : 1241 - 1249
12345