Simulation using random numbers

08/03/2018
by   Illia O. Teplytskyi, et al.
0

This article is devoted to methods of construction and study of stochastic models based on Monte Carlo method. A model of Brownian motion, the construction and processing which brings to a world of random numbers and mathematical statistics, promotes understanding of the probability distribution, in particular illustrates two common distributions: uniform and normal.

READ FULL TEXT
research
01/18/2018

Monte Carlo Computation for Generalized Linear Model

Monte Carlo method is a broad class of computational algorithms that rel...
research
11/20/2012

Random Input Sampling for Complex Models Using Markov Chain Monte Carlo

Many random processes can be simulated as the output of a deterministic ...
research
03/19/2010

Optimisation of a Crossdocking Distribution Centre Simulation Model

This paper reports on continuing research into the modelling of an order...
research
09/11/2018

Hyperbolic normal stochastic volatility model

For option pricing models and heavy-tailed distributions, this study pro...
research
05/27/2023

Mathematical model of mating probability and fertilized egg production in helminth parasites

In the modeling of parasite transmission dynamics, understanding the rep...
research
08/19/2020

Monte Carlo construction of cubature on Wiener space

In this paper, we investigate application of mathematical optimization t...
research
03/15/2019

Limits of Sums for Binomial and Eulerian Numbers and their Associated Distributions

We provide a unified, probabilistic approach using renewal theory to der...

Please sign up or login with your details

Forgot password? Click here to reset