Bivariate wiener process
WebJan 9, 2024 · A novel, general two-sample hypothesis testing procedure is established for testing the equality of tail copulas associated with bivariate data. More precisely, using a martingale transformation of a natural two-sample tail copula process, a test process is constructed, which is shown to converge in distribution to a standard Wiener process. WebAug 1, 2024 · Hajiha et al. (2024) used the Wiener process to analyze competing degradation processes under dynamic operation conditions. Liu et al. (2024) constructed a bivariate gamma process by trivariate reduction method to build condition-based maintenance policies.
Bivariate wiener process
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WebMar 1, 2024 · A two-stage degradation model is proposed, in which a correlated bivariate Wiener process and a univariate Wiener process are adopted to model the system … WebDec 20, 2012 · The convergence of the method is theoretically proved for bivariate diffusion processes. We derive explicit expressions for these and other quantities of interest in the case of a bivariate Wiener process, correcting previous misprints appearing in the literature. Finally we illustrate the application of the method through a set of examples.
WebXiaolin Wang, Bo Guo, Zhijun Cheng, Residual life estimation based on bivariate Wiener degradation process with time-scale transformations, Journal of Statistical Computation and Simulation, 10.1080/00949655.2012.719026, 84, 3, (545-563), (2012). WebThis article concerns the optimization of measurement plans in the design of bivariate degradation tests for bivariate Wiener processes. After describing an unbalanced …
WebA bivariate Wiener process model with measurement errors was used to model the degradation measurements. A two-stage method and the Markov chain Monte Carlo (MCMC) method were combined to estimate the unknown parameters in sequence. Results from a numerical example about fatigue cracks show that the proposed method is valid as WebApr 1, 2016 · The convergence of the method is theoretically proved for bivariate diffusion processes. We derive explicit expressions for these and other quantities of interest in the case of a bivariate Wiener process, correcting previous misprints appearing in the literature. Finally we illustrate the application of the method through a set of examples.
WebOct 1, 2024 · One advantage of Wiener process with drift is that the first passage time can be easily obtained [16], [17], [18]. Moreover, hitting times of bivariate Wiener process models have also been studied [19]. However, a distinct feature of Wiener process with drift model is that the sample path is not necessarily monotonic, which limits its ...
WebA mode is the means of communicating, i.e. the medium through which communication is processed. There are three modes of communication: Interpretive Communication, … easybiocloudWebJul 1, 2013 · A bivariate Wiener process with random effects is used to model the evolution of two performance characteristics, which are dependent on each other. A … cuny schools with education majorsWebJan 24, 2024 · ula method, bivariate degradation process models based on the Wiener process, the gamma process, and the in verse Gaussian process are considered in … cuny schools with communication majorsWebJul 10, 2013 · A bivariate Wiener process model with measurement errors was used to model the degradation measurements. A two-stage method and the Markov chain Monte … cuny schools with dental programsWebThis paper presents a model based on a bivariate Wiener process in which one component represents the marker and the second, which is latent (unobservable), … cuny schools with engineering majorsWebDec 28, 2016 · A bivariate Wiener process with random effects is used to model the evolution of two performance characteristics, which are dependent on each other. A bootstrap method is used to estimate the initial parameters with history of degradation data. Once the new degradation information for an individual component is available, the hyper … easy bins southlandWebApr 23, 2024 · In this case, X = (X0, X1, …) is called the simple symmetric random walk. The symmetric random walk can be analyzed using some special and clever combinatorial arguments. But first we give the basic results above for this special case. For each n ∈ N +, the random vector Un = (U1, U2, …, Un) is uniformly distributed on { − 1, 1}n, and ... easy biochem college course online