https://github.com/logandgraham/stochasticprocesses
A lightweight, efficient package for simulating stochastic processes on various domains.
https://github.com/logandgraham/stochasticprocesses
graphs lightgraphs random-walk simulation stochastic-processes
Last synced: 3 months ago
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A lightweight, efficient package for simulating stochastic processes on various domains.
- Host: GitHub
- URL: https://github.com/logandgraham/stochasticprocesses
- Owner: LoganDGraham
- License: mit
- Created: 2020-10-12T14:47:57.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2020-12-15T00:07:40.000Z (about 5 years ago)
- Last Synced: 2025-10-21T11:58:46.048Z (3 months ago)
- Topics: graphs, lightgraphs, random-walk, simulation, stochastic-processes
- Language: Julia
- Homepage:
- Size: 1.24 MB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# StochasticProcesses
A lightweight, efficient package for simulating stochastic processes on various domains.
## Installation
Installation is straightforward: enter Pkg mode by hitting `]`, and then run
```julia-repl
(v1.5) pkg> add StochasticProcesses
```
## Basic Examples
Bring `StochasticProcesses`'s exported items into the namespace by running
```julia-repl
using StochasticProcesses
```
### Random Walk
Instantiate a one-dimensional random walk:
```julia-repl
rw = RandomWalk(1)
```
Simulate 20 realizations of the random walk `rw` and plot the results:
```julia-repl
plot(rw)
```
A pop-up window should render something like the following:
### Poisson Process
Instantiate a homogeneous Poisson process with arrival rate `1.0`:
```julia-repl
pp = PoissonProcess(1.0)
```
Simulate 10 realizations of the Poisson process `pp` over the time interval `[0, 30]`, and
plot the results:
```julia-repl
plot(pp)
```
A pop-up window should render something like the following:
