WolfRiverPlots.jl is a versatile plotting package built in the Julia programming language. The package consists of specific plotting recipes, designed to streamline data visualization and enhance the process of statistical analysis.
Currently we offer one function, and we will add more with time.
confidenceplot(): This function is designed to create vertical confidence plots. These plots can be used to visualize regression coefficients and their confidence intervals visually.
To install WolfRiverPlots.jl, you can use Julia's package manager. Here is the command:
using Pkg
Pkg.add("WolfRiverPlots")After installing WolfRiverPlots.jl, you can include it in your Julia script using the following command:
using WolfRiverPlots- Confidence plots:
# ε contains variation relative to x-estimates
plot_confidence(x, y, ε)The following examples provide a basic idea of how to use the functions provided by WolfRiverPlots.jl. Before proceeding, ensure that you've installed WolfRiverPlots.jl and imported it into your Julia script using using WolfRiverPlots along with Plots.jl.
using WolfRiverPlots
using Distributions, Random
using Plots
########
# Data #
########
Random.seed!(1203)
x = randn(7)
y = repeat([""], 7)
y = map(x -> randstring('A':'Z', 2), y)
ε = rand(Uniform(0.1,0.25), 7)
########
# Plot #
########
plot_confidence(x, y, ε,
title = "Confidence Plot\n",
xlabel = "Effect Size",
ylabel = "Variables")
Contributions to WolfRiverPlots.jl are welcome and appreciated. If you'd like to contribute, please fork the repository and make changes as you'd like. If you have any questions or issues, feel free to open an issue on the repository.
WolfRiverPlots.jl is licensed under the GNU AFFERO GENERAL PUBLIC LICENSE. For more information, please refer to the LICENSE file in the repository.
If you have any problems or questions using WolfRiverPlots.jl, please open an issue on the GitHub repository. We'll be happy to help!