Showing papers on "Stochastic simulation published in 1974"

A continuous random network model with three-fold coordination

Abstract: A continuous random network with three-fold coordination has been constructed. The radial distribution function and density have been measured end the coherent scattered intensity computed. The agreement between these and experimental results for amorphous As is good.

Diffusive random process approximation in certain nonstationary statistical problems of physics

Abstract: The review considers, on the basis of a unified approach, the problem of Brownian motion in nonlinear dynamic systems, including a linear oscillator acted upon by random forces, parametric resonance in an oscillating system with random parameters, turbulent diffusion of particles in a random-velocity field, and diffusion of rays in a medium with random inhomogeneities of the refractive index. The same method is used to consider also more complicated problems such as equilibrium hydrodynamic fluctuations in an ideal gas, description of hydrodynamic turbulence by the method of random forces, and propagation of light in a medium with random inhomogeneities. The method used to treat these problems consists of constructing equations for the probability density of the system or for its statistical moments, using as the small parameter the ratio of the characteristic time of the random actions to the time constant of the system (in many problems, the role of the time is played by one of the spatial coordinates). The first-order approximation of the method is equivalent to replacement of the real correlation function of the action by a δ function; this yields equations for the characteristics in closed form. The method makes it possible to determine also higher approximations in terms of the aforementioned first-order small parameter.

Blockinq in simular experimental designs

Abstract: The repetitive use of generated and/or recorded sequences in the model encounters comprising simular experimental designs has been a suggested technique of simulation methodology. The application of the technique has been deemed compatible with the experimental statistician's concept of blocking. The present paper verifies this compatibility, though notes that the resulting block effect must properly be interpreted as a variance component, or random block effect. A corollary to this result is a delineated procedure for selecting the random number seeds for successive encounters with a dynamic, stochastic simulation model, the procedure providing a proper measure of experimental error. The applicability of the established methodology of the design and analysis of experiments to systemic science via simulation modelling is thereby assured.

Stochastic simulation of chemical reaction by digital computer, I. The model

Abstract: A stochastic model of complex chemical reactions is outlined. A discrete Markov process corresponds to the complex chemical reaction in the model i.e. the concentrations of the components are discrete quantities. The differences between the stochastic and deterministic models are discussed.

Representation of random noise by random pulses

Abstract: The problem of modeling random noise by a sequence of random pulses that result from the random occurrence of similar events of randomly varying duration and strength is considered. It is illustrated how the statistical properties of the distribution of noise‐producing events may be inferred from a knowledge of the power spectrum of the noise and the characteristic shape of the pulses.

Distribution functions in stochastic programs with recourse: A parametric analysis

Abstract: This paper studies the behavior of the optimum value of a two-stage stochastic program with recourse (random right-hand sides) as the mean and covariance matrices defining the random variables in the program are perturbed. Several results for convex programs are developed and are used to study the effect such perturbations have on the regularity properties of the stochastic programs. Cost associated with incorrectly specifying the mean and covariance matrices are discussed and estimated. A stochastic programming model in which the random variable is dependent on the first-stage decision is presented.

Random collision processes and their limiting distribution using the discrimination information

Abstract: By analogy with statistical mechanics random collision processes are considered. In two cases we derive their limiting distributions using discrimination information. In one case the limiting distribution is unique and in the other one the family of limiting distributions is an exponential family. RANDOM COLLISION PROCESS; DISCRIMINATION INFORMATION; BOLTZMANN'S H-THEOREM; EXPONENTIAL FAMILY; DETERMINISTIC RANDOM MATING

AUTASIM: A system for computerred Assembly of Simulation Models

Abstract: The AUTASIM System (Automated Assembly of Simulation Models) is described. The system is designed to rapidly assemble discrete event, stochastic simulation models of node network systems. Systems of this type are distribution systems, plant operations, systems for the provision of services, transportation systems, and combinations of these. Models can be used for comparative analysis of new concepts and proposed systems with other systems.The main AUTASIM components are a Module Library of computer programs, a program called the Model Assembler and a Model Description Language. The Library contains functional and simulation service modules which are the “building blocks” for the simulation models created. The Model Assembler program reads a coded model description, selects the required modules from the Library, and creates the necessary linkage routines for a complete model program.The Model Description Language, AUTASCRIPT, is defined. The operation of the FORTRAN coded Model Assembler and linkage control programs is described, as is the GASP based model simulation control.

Random hypertrees and hyperforests

Abstract: We prove the asymptotic normality of the number of edges in a random hypertree and a limiting Poisson law for the number of components in a random hyperforest.

An improved exceedance theory for combined random stresses

Abstract: An extension is presented of Rice's classic solution for the exceedances of a constant level by a single random process to its counterpart for an n-dimensional vector process. An interaction boundary, analogous to the constant level considered by Rice for the one-dimensional case, is assumed in the form of a hypersurface. The theory for the numbers of boundary exceedances is developed by using a joint statistical approach which fully accounts for all cross-correlation effects. An exact expression is derived for the n-dimensional exceedance density function, which is valid for an arbitrary interaction boundary. For application to biaxial states of combined random stress, the general theory is reduced to the two-dimensional case. An elliptical stress interaction boundary is assumed and the exact expression for the density function is presented. The equations are expressed in a format which facilitates calculating the exceedances by numerically evaluating a line integral. The behavior of the density function for the two-dimensional case is briefly discussed.

Simulation of predator—prey relationships in an acarine system†

Abstract: Simulation with a computer can be an aid in the analysis of complex ecological processes. When such processes bear upon the behaviour of individual plants or animals, they often depend on chance variables. Such stochastic processes cannot be correctly simulated with a deterministic model, when there are non-linear relationships between output variables and chance variables. On the other hand, simulation with a stochastic model using a random function generator has to be repeated several times to obtain reliable expectation values of the output variables. A method is described for simulation of stochastic processes in one run, which provides acceptable expectation values. The method is applied in a program for simulation of a predation process, which occurs when the predacious mite, Typhiodromus occidentalis, preys on eggs of the spider mite Tetranychus urticae. The results are compared with those obtained by regular deterministic and stochastic simulation.

On the generation of random numbers with at choice distribution

Abstract: This paper deals with a method supplying truly random numbers in cycle-free sequences of any length and with a specified statistical distribution as desired. The method is based on an appropriate randomness-conserving rearrangement of truly random numbers delivered by a random process. Here the radioactive decay of nuclei is employed as the random process that produces a basic set of truly random numbers with a Poisson distribution. However, any other random process can be used with the method. The paper contains the theory and some essential points of programming for a computer.

A note on effects of digital approximation in linear models

Abstract: Gray, Lewis and Poirot (1971) introduced a method of partially correcting for errors due to truncation of the values of a random vector. For normally distributed random vectors, they showed that their estimator, Z, is an MLE for μ. In this note the bias error for truncated (discretized) random variables is discussed, and it is shown that the average of corrected sample observations is not an MLE for the mean of the underlying distribution.