Titlebook: Advances in the Statistical Sciences: Stochastic Hydrology; Volume IV Festschrif Ian B. MacNeill,Gary J. Umphrey,A. Ian McLeod Book 1987 D.

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https://doi.org/10.1007/978-1-4757-9826-5ual particles are governed by nonhomogeneous diffusions with random coefficients..The implementation of this complex stochastic model involves optimal smoothing of configuration and estimation of Ornstein-Uhlenbeck parameters from limited engineering data. Preliminary simulations are reported.

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A Markov Model for Sedimentation: Fundamental Issues and Insights,ual particles are governed by nonhomogeneous diffusions with random coefficients..The implementation of this complex stochastic model involves optimal smoothing of configuration and estimation of Ornstein-Uhlenbeck parameters from limited engineering data. Preliminary simulations are reported.

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A Stochastic Modelling of Tidal Current Measurements,A model was fitted. It was found that the actual differenced residuals are related to those previous ones with time lags of 16, 17, 21, 33 or 34 hours. Such time lags do not correspond to any known tidal periodicities. It is suggested that other forcing, due to meteorological phenomena for example,

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Advances in the Statistical Sciences: Stochastic HydrologyVolume IV Festschrif

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Book 1987ant, and Sandy Tamowski. This work has been printed from "camera ready" copy produced by our Vax 785 computer and QMS Lasergraphix printers, using the text processing software TEX. At the initiation of this project, we were neophytes in the use of this system. Thank you, J ackie, Lise, and Sandy, fo

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A Markov Model for Sedimentation: Fundamental Issues and Insights, governed by a system of first-order non-linear differential equations. Non-linearity and finite precision conspire to produce chaotic and unpredictable trajectories. Our model replaces this chaos of complex interactions by the formal chaos of stochastic processes..The model utilizes a family of ind

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