RandomWalker Wiki - Home

📖 What is RandomWalker?

RandomWalker is a comprehensive R package that provides a unified, tidyverse-compatible interface for generating random walks of various types. Whether you’re modeling stock prices, simulating particle movements, or exploring stochastic processes, RandomWalker makes it easy to:

• Generate random walks from 27+ different probability distributions
• Create walks in 1D, 2D, or 3D space
• Visualize walks with beautiful, interactive plots
• Compute comprehensive statistical summaries
• Work seamlessly with tidyverse tools

🚀 Quick Navigation

💡 Key Features

📦 Package Information

• Current Version: 1.0.0.9000 (development)
• CRAN Release: 1.0.0
• License: MIT
• Authors: Steven P. Sanderson II, MPH & Antti Rask
• R Version Required: >= 4.1.0

🔗 External Links

• Package Website: https://www.spsanderson.com/RandomWalker/
• GitHub Repository: https://github.com/spsanderson/RandomWalker
• Issue Tracker: https://github.com/spsanderson/RandomWalker/issues
• CRAN Page: https://cran.r-project.org/package=RandomWalker

📚 Learning Path

If you’re new to RandomWalker, we recommend following this learning path:

1. Installation - Install the package
2. Quick Start Guide - Learn the basics
3. Automatic Random Walks - Use rw30() for quick results
4. Continuous Distribution Generators - Explore different distributions
5. Visualization Guide - Create beautiful plots
6. Statistical Analysis Guide - Analyze your walks
7. Use Cases and Examples - See real-world applications

🎯 Common Use Cases

• Finance: Model stock price movements with Geometric Brownian Motion
• Physics: Simulate particle diffusion with Brownian Motion
• Biology: Model organism movement patterns
• Computer Science: Generate test data for algorithms
• Education: Teach probability and stochastic processes
• Research: Explore theoretical properties of random walks

🤝 Getting Help

• Documentation: Read the vignettes with vignette("getting-started") or vignette("home")
• Issues: Report bugs at the GitHub Issues page
• Discussions: Ask questions in GitHub Discussions
• Email: Contact the maintainer at spsanderson@gmail.com

🌟 Citation

If you use RandomWalker in your research, please cite it:

citation("RandomWalker")

Example: Quick Start

Here’s a quick example to get you started with RandomWalker:

# Generate 30 random walks
walks <- rw30()

# View the first few rows
head(walks)
#> # A tibble: 6 × 3
#>   walk_number step_number      y
#>   <fct>             <int>  <dbl>
#> 1 1                     1 0     
#> 2 1                     2 0.319 
#> 3 1                     3 0.445 
#> 4 1                     4 0.189 
#> 5 1                     5 0.0557
#> 6 1                     6 0.120

# Visualize the walks
visualize_walks(walks)

# Get summary statistics
walks |> 
  summarize_walks(.value = y) |>
  head()
#> Warning: There was 1 warning in `dplyr::summarize()`.
#> ℹ In argument: `geometric_mean = exp(mean(log(y)))`.
#> Caused by warning in `log()`:
#> ! NaNs produced
#> # A tibble: 1 × 16
#>   fns   fns_name dimensions mean_val median range quantile_lo quantile_hi
#>   <chr> <chr>         <dbl>    <dbl>  <dbl> <dbl>       <dbl>       <dbl>
#> 1 rw30  Rw30              1   -0.714 -0.606  48.4       -14.6        12.2
#> # ℹ 8 more variables: variance <dbl>, sd <dbl>, min_val <dbl>, max_val <dbl>,
#> #   harmonic_mean <dbl>, geometric_mean <dbl>, skewness <dbl>, kurtosis <dbl>

Ready to get started? Explore the package documentation and other vignettes to begin your journey with RandomWalker!