---
title: "RandomWalker Wiki - Home"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{RandomWalker Wiki - Home}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r setup, echo=FALSE, message=FALSE}
library(RandomWalker)
```

```{r logo, echo=FALSE, out.width="147px", out.height="170px"}
#| fig.alt: >
#|   RandomWalker package logo featuring a hexagonal design with abstract paths
#|   representing random walks, symbolizing the package's functionality for generating
#|   and analyzing stochastic processes.
knitr::include_graphics("../man/figures/logo.png")
```

Welcome to the **RandomWalker** Wiki! This comprehensive guide will help you master the RandomWalker R package for generating, visualizing, and analyzing random walks.

## 📖 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

### Getting Started

-   **Installation** - How to install the package
-   **Quick Start Guide** - Get up and running in minutes
-   **Basic Concepts** - Understanding random walks

### Function Guides

-   **Automatic Random Walks** - Using `rw30()` for instant results
-   **Continuous Distributions** - Normal, Brownian, Gamma, Beta, and more
-   **Discrete Distributions** - Binomial, Poisson, Geometric, and more
-   **Multi-Dimensional Walks** - Working in 2D and 3D space

### Advanced Topics

-   **Visualization Guide** - Creating beautiful plots
-   **Statistical Analysis Guide** - Computing summary statistics
-   **Use Cases and Examples** - Real-world applications

### Reference

-   **API Reference** - Complete function documentation
-   **FAQ** - Frequently Asked Questions
-   **Troubleshooting** - Common issues and solutions

### Contributing

-   **Contributing Guide** - How to contribute to the project

## 💡 Key Features

### 🎲 27+ Distribution Types

Generate random walks from a wide variety of probability distributions including:

-   **Continuous**: Normal, Brownian Motion, Geometric Brownian Motion, Beta, Cauchy, Chi-Squared, Exponential, F, Gamma, Log-Normal, Logistic, Student's t, Uniform, Weibull
-   **Discrete**: Binomial, Discrete, Geometric, Hypergeometric, Multinomial, Negative Binomial, Poisson
-   **Custom**: Define your own displacement functions

### 📐 Multi-Dimensional Support

-   1D random walks for time series analysis
-   2D random walks for spatial modeling
-   3D random walks for particle physics simulations

### 📊 Rich Visualizations

-   Static plots with ggplot2
-   Interactive visualizations with ggiraph
-   Support for multiple walk comparison
-   Customizable aesthetics

### 📈 Statistical Analysis

-   Comprehensive summary statistics
-   Cumulative functions (sum, product, min, max, mean)
-   Confidence intervals
-   Running quantiles
-   Euclidean distance calculations
-   Harmonic and geometric means
-   Skewness and kurtosis

### 🔧 Tidyverse Compatible

Works seamlessly with:

-   `dplyr` for data manipulation
-   `tidyr` for data reshaping
-   `ggplot2` for custom visualizations
-   Pipe operators (`|>` and `%>%`)

## 📦 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](https://github.com/spsanderson/RandomWalker/issues) page
-   **Discussions**: Ask questions in [GitHub Discussions](https://github.com/spsanderson/RandomWalker/discussions)
-   **Email**: Contact the maintainer at spsanderson\@gmail.com

## 🌟 Citation

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

```{r citation, eval=FALSE}
citation("RandomWalker")
```

## Example: Quick Start

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

```{r quick_example}
# Generate 30 random walks
walks <- rw30()

# View the first few rows
head(walks)
```

```{r visualize_example, fig.width=7, fig.height=4}
#| fig.alt: >
#|   Visualization of multiple random walks generated by rw30()
# Visualize the walks
visualize_walks(walks)
```

```{r summary_example}
# Get summary statistics
walks |> 
  summarize_walks(.value = y) |>
  head()
```

------------------------------------------------------------------------

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