pearson.diagram

Overview

The pearson.diagram package provides tools to visualize different statistical distributions by plotting skewness and kurtosis values on a Pearson Diagram. This package is useful for comparing multiple distributions, calculating skewness and kurtosis for unknown data distributions, and identifying data characteristics in terms of central moments. The Pearson diagram illustrates the relationship between the skewness and kurtosis of several probability distributions. The $x-\text{axis}$ shows the square of skewness, while the $y-\text{axis}$ shows the kurtosis. This figure helps in visually identifying the properties of various distributions and how they fit in the skewness-kurtosis space.

Skewness $\beta_{1}=\mu_{3}^{2}/\mu_{2}^{3}$

Kurtosis $\beta_{2}=\mu_{4}/\mu_{2}^{2}$

Key features of the package include:

• Plotting of known and user-defined distributions on a Pearson Diagram
• Efficient skewness and kurtosis calculations using Rcpp
• Bootstrap analysis to understand variability in skewness and kurtosis estimates
• Handling of extreme outliers for robust data visualization
• Flexibility in customizing plot appearance

The package follows the S3 object-oriented programming paradigm for flexibility and extensibility.

Installation

To install the pearson.diagram package, clone the repository and build the package using the following commands:

# Clone the repository from GitHub

# Install the package
devtools::install_github("renswickd/R-Package-for-Pearson-Diagram")

Getting Started

Once installed, load the package and explore its main functions.

library(pearson.diagram)

Main Function: plot_diagram

The primary function for visualizing data on the Pearson Diagram is plot_diagram. It allows plotting both known distributions and user-defined data distributions.

• This is the main function that generates the Pearson diagram. It accepts a variety of input parameters, including a Pearson object, custom input data, and option to enable bootstrap functionality or hover-over interactivity.
• If custom (unknown) data is provided, it calculates the square of skewness and kurtosis for the data points and highlights them on the plot. Otherwise, the function generates a pearson plot with known distribution families and no extra points.

Contributing

If you find a bug or would like to request a feature, please create an issue on GitHub. Pull requests are welcome; please make sure that the code is thoroughly tested and documented.

License

This package is licensed under the MIT License. See the LICENSE file for more details.

Acknowledgments

The pearson.diagram package leverages Rcpp for high-performance computation and ggplot2 for flexible data visualization. We thank the R community for their invaluable support and resources.