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Runoff as a Stochastic Process
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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Parallel implementation of stochastic simulation for large-scale cellular processes [PDF]
Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional ...
Kevin Burrage +6 more
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Adaptive Robust Efficient Methods for Periodic Signal Processing Observed with Colours Noises
In this paper, we consider the problem of robust adaptive efficient estimating a periodic signal observed in the transmission channel with the dependent noise defined by non-Gaussian Ornstein-Uhlenbeck processes with unknown correlation properties ...
Evgeny Pchelintsev +2 more
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MEXIT : Maximal un-coupling times for stochastic processes [PDF]
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. +13 more
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Perpetual Futures for Stocks: The SpaceX Pre-IPO Market
Robert Shiller proposed perpetual futures in 1993 to create derivative markets for assets that are illiquid or whose price cannot be observed directly. Cryptocurrency markets later built the instrument under a different funding rule.
Aditya Gupta, Nicholas G. Polson
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Measuring the Moment and the Magnitude of the Abrupt Change of the Gaussian Process Bandwidth
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 +4 more
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Strong Consistency of Incomplete Functional Percentile Regression
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 +3 more
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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 +2 more
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Estimation of Accuracy and Reliability of Models of φ-sub-Gaussian Stochastic Processes in Spaces
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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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 +4 more
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