Applied Probability and Statistical Inference in Reliability Engineering
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Probability and Statistics".
Deadline for manuscript submissions: 28 February 2025 | Viewed by 6104
Special Issue Editors
Interests: nonparametric statistical inference; statistical reliability theory; statistical process control; order statistics; applied probability
Special Issues, Collections and Topics in MDPI journals
Interests: model selection; applied probability; reliability theory; medical statistics; time series; biostatistics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Probability theory and statistics play a fundamental role in the research of various scientific fields, such as engineering, computer science, medicine, biology, or economics. Several statistical methods and probabilistic approaches, such as order statistics, Markov chain imbedding, computational statistics, generating functions approaches, or nonparametric statistics have attracted a considerable research interest during recent decades.
The aim of this Special Issue is to provide some evidence which reflects the importance of statistical techniques and probabilistic modelling in applied scientific areas, related to reliability engineering. We welcome articles establishing theoretical methodologies in these fields, but papers providing interesting and innovative applications, including solutions of important practical problems and case studies, of probability and statistics shall also be considered. Thus, the Special Issue is expected to be a collective work by a number of leading researchers and practitioners in their respective fields of expertise and, in general, experts who have been working at the forefront of applied probability, statistics, and reliability theory.
Dr. Ioannis S. Triantafyllou
Prof. Dr. Karagrigoriou Alexandros
Guest Editors
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Keywords
- reliability modelling
- nonparametric statistics
- probabilistic methods
- statistical models and methods
- reliability and risk analysis
- stochastic models and methods
- probabilistic models in reliability
- nonparametric methods in reliability
- software reliability
- Markov and semi-Markov processes in reliability
- stochastic problems in reliability
- multi-state systems
- maintenance policies in reliability
- order statistics in reliability
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