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
- Almost functions need the package "Distribution" for execute.
- You has that declare a vector of functions in each leyaer for neural process execute.
- 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.