Kipngeno Kirui

Hey @JeromeM75 , how did you manage to load this data? Did you get a solution?

@matbesancon Is this really necessary for functions like `rand()` and `randn()`?

Yes. I have seen what you mean. This means that I need to use the package `Random` for this. Thank you. I will implement immediately.

@matbesancon I will close this issue then because I have already included using Random RNG in the package through `MersenneTwister`.

According to Julia's documentation, every function which performs a random sampling should take in a parameter the Random Number Generator (which is usually a subtype of Random.AbstractRNG. Also, random number...

https://docs.julialang.org/en/v1/stdlib/Random/ I used the concept in the above julia documentation. Another option was to use `Random.seed!()`.

Both MersenneTwister and Random.seed!() works in a similar manner. Consider the below, `julia> MersenneTwister(01102019) == Random.seed!(01102019)` `true`

In https://github.com/kirui93/ScenTrees.jl/blob/master/src/StochPaths.jl, `rng = MersenneTwister(0101219)` and I have passed it as an argument of `randn()` in all the functions.

Hello @matbesancon, do you suggest using as in the following example instead of the above? ``` julia> rand(rng::AbstractRNG, 3,2) 3×2 Array{Float64,2}: 0.496169 0.449182 0.732 0.875096 0.299058 0.0462887 ```

For the stochastic approximation process, we need a function that doesn't take any inputs. That is why we coded these examples without any inputs. This is why we preferred to...