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)

Importing RandomProcesses and PyPlot

using RandomProcesses, PyPlot, Distributions

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

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

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

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 [email protected]. I would also like to know out of curiosity in which projects the patent is being used.