微不足道
发表于 2025-3-26 22:18:38
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马赛克
发表于 2025-3-27 03:12:21
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Dysplasia
发表于 2025-3-27 09:06:15
https://doi.org/10.1007/978-3-658-39961-0The following problem was raised by Alfaro (1979). A submarine cable has to be laid across the straits of Gibraltar. How can its length be predicted if the depth of the sea floor has been measured sparsely along its trajectory?
Insufficient
发表于 2025-3-27 10:27:16
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弓箭
发表于 2025-3-27 14:13:07
Mai Yamagami,James W. TollefsonThe integral range is a simple and powerful tool that helps to quantify the statistical fluctuations of a stochastic model. Their knowledge is required to ensure the correctness of any computer program supposed to produce simulations of the model.
affinity
发表于 2025-3-27 18:35:28
https://doi.org/10.1007/978-981-16-3001-9The problem addressed in this chapter is the simulation of a distribution . on .. In the case when the state-space Ω has an abstract setting or a complicated shape, the algorithms presented in the previous chapter may not be directly applicable. More general algorithms are then required.
顾客
发表于 2025-3-28 00:29:36
Overview of Mobile Communication,The previous chapter highlighted the difficulties in determining the rate of convergence of an iterative Markov algorithm quantitatively. This is very frustrating as the only problem is to generate one state from the target distribution: then it suffices to run the transition kernel from that state to produce as many as desired.
同步左右
发表于 2025-3-28 03:35:25
Advanced Navigation: The Popup MenuThis chapter is devoted to two models constructed from gaussian random functions. The first one is an excursion set obtained by thresholding a gaussian random function. The second one is a step function that results from the joint thresholding of two or more gaussian random functions. It is called a plurigaussian random function.
cocoon
发表于 2025-3-28 08:48:35
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抗生素
发表于 2025-3-28 12:27:36
Investigating stochastic modelsIn this chapter we review the statistical description of several classes of stochastic models (random functions, random sets, random point processes and random populations of objects) that will be encountered throughout this book. This review is preceded by a brief reminder about probability calculus.