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RandomProcesses.jl

Introduction

RandomProcesses.jl is a package for simulling stochastics processes in Julia in a easy way.

At the moment the package has 8 functions that simulling the following stochastic processes:

  • SARMA
  • Ramdom Walk
  • Weiner
  • Martingale
  • Galton Watson
  • Markov Chain
  • Poisson
  • Neural (simuling the results of neural network)

Exemples

Importing RandomProcesses and PyPlot

using RandomProcesses, PyPlot, Distributions

Random Walk

for _ in 1:5
  plot(RandomWalk())
end

RW.png

Poisson Process

for _ in 1:5
  plot(PoissonProcess())
end

Poisson.png

Neural Process

function f(x)
    return exp.(x)./(1 .+ exp.(x))
end

function g(x)
    return sum(x)
end

for _ in 1:5
    plot(NeuralProcess(Activate = [f, g], Len = 30))
end

Neural.png

Coments

  1. Almost functions need the package "Distribution" for execute.
  2. You has that declare a vector of functions in each leyaer for neural process execute.
  3. This is my first package, please have pacience. Send criticisms and suggestions to joaquimacbermudes@gmail.com. I would also like to know out of curiosity in which projects the patent is being used.