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Applications of Dynamic-Equilibrium Continuous Markov Stochastic Processes to Elements of Survival Analysis
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作者 Eugen Mamontov Ziad Taib 《Journal of Applied Mathematics and Physics》 2019年第1期55-71,共17页
In this article, we summarize some results on invariant non-homogeneous and dynamic-equilibrium (DE) continuous Markov stochastic processes. Moreover, we discuss a few examples and consider a new application of DE pro... In this article, we summarize some results on invariant non-homogeneous and dynamic-equilibrium (DE) continuous Markov stochastic processes. Moreover, we discuss a few examples and consider a new application of DE processes to elements of survival analysis. These elements concern the stochastic quadratic-hazard-rate model, for which our work 1) generalizes the reading of its It? stochastic ordinary differential equation (ISODE) for the hazard-rate-driving independent (HRDI) variables, 2) specifies key properties of the hazard-rate function, and in particular, reveals that the baseline value of the HRDI variables is the expectation of the DE solution of the ISODE, 3) suggests practical settings for obtaining multi-dimensional probability densities necessary for consistent and systematic reconstruction of missing data by Gibbs sampling and 4) further develops the corresponding line of modeling. The resulting advantages are emphasized in connection with the framework of clinical trials of chronic obstructive pulmonary disease (COPD) where we propose the use of an endpoint reflecting the narrowing of airways. This endpoint is based on a fairly compact geometric model that quantifies the course of the obstruction, shows how it is associated with the hazard rate, and clarifies why it is life-threatening. The work also suggests a few directions for future research. 展开更多
关键词 Non-Homogeneous Continuous markov stochastic process Invariant process Dynamic Equilibrium Diffusion stochastic process Ito stochastic Ordinary Differential Equation Survival Analysis Hazard Rate Obstructive Lung Disease
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A GMRP Approach for Reliability Analysis of Repairable Systems
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作者 Wang Jing & Yang DeliInst. of Systems Engineering, Dalian University of Technology. Dalian 116023, China 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 1991年第2期44-54,共11页
We propose here a mathematical approach for the study of repairable systems with arbitrary distributions. The idea is to define a new type of stochastic process, called a generalized Markov renewal process (GMRP). whi... We propose here a mathematical approach for the study of repairable systems with arbitrary distributions. The idea is to define a new type of stochastic process, called a generalized Markov renewal process (GMRP). which may describe the transition behavior of the stochastic process at non-regenerative points. In the paper an analytical method for the GMRP is put forward and the formulas are then presented for reliability analysis of repairable systems which can be described by a GMRP with finite states. A signal flow graph technique for system modeling is also summarized here. Finally- an analytical model to evaluate the reliability of a m-out-of- n.G system with general repair-time distribution is developed by means of the GMRP approach. 展开更多
关键词 Reliability evaluation markov process stochastic processes.
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