Results 21 to 30 of about 5,790,115 (297)

Runoff as a Stochastic Process

International Journal of Mathematics and Computers in Simulation, 2022
Runoff stationary critical flow is investigated as a stochastic process by means of two routing simulation models, a stream confluence, which has beens interpreted as a Marcus- Lushnikov coalescence process, and a channel splitting model, which has ben interpreted as a Markov chain over a regular tree.
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MEXIT : Maximal un-coupling times for stochastic processes [PDF]

, 2018
Classical coupling constructions arrange for copies of the same Markov process started at two dif- ferent initial states to become equal as soon as possible.
Rosenthal, Jeff S., Rosenthal, Jeffrey S., Rosenthal, Jeffrey S, Kendall, Wilfrid S, Ernst, Philip A., Kendall, W. S., Roberts, Gareth O., Jeffrey S. Rosenthal, Philip A. Ernst, Roberts, Gareth O, Kendall, Wilfrid S., Wilfrid S. Kendall, Gareth O. Roberts, Ernst, Philip A   +13 more
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A posteriori error estimation for stochastic static problems [PDF]

, 2014
To solve stochastic static field problems, a discretization by the Finite Element Method can be used. A system of equations is obtained with the unknowns (scalar potential at nodes for example) being random variables. To solve this stochastic system, the
MAC, Hung, CLENET, Stephane
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Measuring the Moment and the Magnitude of the Abrupt Change of the Gaussian Process Bandwidth

Measurement Science Review, 2019
The maximum likelihood algorithm is introduced for measuring the unknown moment of abrupt change and bandwidth jump of a fast-fluctuating Gaussian random process.
Chernoyarov Oleg, Marčokova Mariana, Salnikova Alexandra, Maksimov Maksim, Makarov Alexander   +4 more
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Strong uniform consistency rates of conditional quantile estimation in the single functional index model under random censorship

Dependence Modeling, 2018
The main objective of this paper is to non-parametrically estimate the quantiles of a conditional distribution in the censorship model when the sample is considered as an -mixing sequence.
Kadiri Nadia, Rabhi Abbes, Bouchentouf Amina Angelika   +2 more
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Estimation of Accuracy and Reliability of Models of φ-sub-Gaussian Stochastic Processes in Spaces

Наукові вісті Національного технічного університету України "Київський політехнічний інститут", 2017
Background. At present, in the theory of stochastic process modeling a problem of assessment of reliability and accuracy of stochastic process model in C(T) space wasn’t studied for the case of inexplicit decomposition of process in the form of a series ...
Oleksandr M. Mokliachuk
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Strong Consistency of Incomplete Functional Percentile Regression

Axioms
This paper analyzes the co-fluctuation between a scalar response random variable and a curve regressor using quantile regression. We focus on the situation wherein the output variable is observed with random missing.
Mohammed B. Alamari, Fatimah A. Almulhim, Ouahiba Litimein, Boubaker Mechab   +3 more
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The System of Facial Recognition in the Infrared Range

Communications, 2020
In this paper, a new approach is introduced upgrading the complex object recognizing monitoring system up to the image processing system capable of operating both in the visible and the infrared wavelength ranges.
Daniil A. Loktev, Alexey A. Loktev, Alexandra V. Salnikova   +2 more
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Uniform Labeled Transition Systems for Nondeterministic, Probabilistic, and Stochastic Processes [PDF]

, 2010
Rate transition systems (RTS) are a special kind of transition systems introduced for defining the stochastic behavior of processes and for associating continuous-time Markov chains with process terms. The transition relation assigns to each process, for
Nicola Michele Loreti, De Nicola, Rocco, Marco Bernardo, Rocco De, Loreti, Michele, Rocco De Nicola, Michele Loreti, Bernardo, Marco, De Nicola, R   +8 more
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Stochastic Patching Process

CoRR, 2016
Stochastic partition models tailor a product space into a number of rectangular regions such that the data within each region exhibit certain types of homogeneity. Due to constraints of partition strategy, existing models may cause unnecessary dissections in sparse regions when fitting data in dense regions.
Xuhui Fan 0001, Bin Li 0015, Yi Wang 0041, Yang Wang 0002, Fang Chen 0001   +4 more
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