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Author:   V.A. Ogorodnikov ,  S.M. Prigarin
Publisher:   Brill
Imprint:   VSP International Science Publishers
Weight:   0.560kg
ISBN:  

9789067641999

ISBN 10:   9067641995
Pages:   240
Publication Date:   February 1996
Recommended Age:   College Graduate Student
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock  
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

Preface STATISTICAL SIMULATION OF DISCRETE GAUSSIAN PROCESSES AND FIELDS WITH A GIVEN CORRELATION STRUCTURE Method of conditional expectations Simulation of the Gaussian vectors with correlation matrix of stationary type Regularization of the algorithm Simulation of autoregressive processes with a desired correlation structure Simulation of stationary Gaussian vector sequences and discrete spatial fields with a given correlation structure Simulation of vector autoregressive sequences Linear transformation method Special algorithms for simulation of homogeneous isotropic discrete Gaussian fields SPECTRAL MODELS OF GAUSSIAN RANDOM FIELDS Construction of spectral models Spectral models of homogeneous vector fields NUMERICAL MODELS OF NON-GAUSSIAN PROCESSES AND FIELDS Consistency conditions of marginal distributions and covariance function Method of inverse distribution functions Models based on stochastic differential equations ''Repetition'' method for simulation of random vectors and processes Method for simulation of random processes and fields on point flows Randomized models of non-Gaussian discrete processes Combined models of non-Gaussian process and fields Numerical models of certain classes of non-Gaussian homogeneous processes and fields CONVERGENCE OF NUMERICAL MODELS OF RANDOM FIELDS IN MONTE CARLO METHOD Introduction Weak convergence of probability measures and random functions Conditions of weak convergence in spaces C and C Convergence of spectral models of the Gaussian homogeneous fields Convergence of one class of non-Gaussian models Remark on allowance for bias of estimates constructed by approximate models Appendix to Chapter 4. Some applications of the Jane-Marcus central limit theorem in statistical simulation SIMULATION OF RANDOM FIELDS IN STOCHASTIC PROBLEMS OF THE ATMOSPHERE--OCEAN OPTICS Numerical modelling of stochastic structure of cumulus clouds for investigation of the solar radiation transfer in the atmosphere Simulation of the undulated sea surface and study of its optical properties by Monte Carlo method HYDROMETEOROLOGICAL APPLICATIONS OF STATISTICAL SIMULATION METHODS Influence of uncertainty in initial data on forecasting accuracy On accuracy of temperature vertical profiles expansion into a series by eigenvectors of sampling covariance matrix Investigation of some features of excursions of air temperature time series Probabilistic models of dry and rainy days time series Probability properties of precipitation amount Approximation of empirical probability distribution of daily rainy precipitation sums Probabilistic model of non-stationary vector sequences in applications to some joint time series and spatial fields of different weather elements APPENDIX 1. SYNOPSIS OF THE THEORY OF STOCHASTIC PROCESSES APPENDIX 2. ON CORRESPONDENCE BETWEEN DISCRETE AND CONTINUOUS LINEAR HOMOGENEOUS STOCHASTIC MODELS APPENDIX 3. CODING OF MULTIPLICATIVE GENERATORS OF PSEUDORANDOM NUMBERS References

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