https://github.com/coatless-rpkg/visualize
Visualize probability distributions values
https://github.com/coatless-rpkg/visualize
graph probability-distribution r
Last synced: 6 months ago
JSON representation
Visualize probability distributions values
- Host: GitHub
- URL: https://github.com/coatless-rpkg/visualize
- Owner: coatless-rpkg
- License: other
- Created: 2017-04-27T19:27:46.000Z (about 8 years ago)
- Default Branch: main
- Last Pushed: 2023-11-14T08:27:43.000Z (over 1 year ago)
- Last Synced: 2024-11-24T14:35:02.114Z (6 months ago)
- Topics: graph, probability-distribution, r
- Language: R
- Homepage: http://r-pkg.thecoatlessprofessor.com/visualize/
- Size: 5.35 MB
- Stars: 4
- Watchers: 2
- Forks: 1
- Open Issues: 3
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "50%"
)
```
# visualize
[](https://github.com/coatless-rpkg/visualize/actions/workflows/R-CMD-check.yaml)
[](https://www.r-pkg.org/pkg/visualize)
[](https://CRAN.R-project.org/package=visualize)
The goal of visualize is to graph the pdf or pmf and highlight what area or
probability is present in user defined locations. Visualize is able to provide
lower tail, bounded, upper tail, and two tail calculations. Supports strict and
equal to inequalities. Also provided on the graph is the mean and variance of
the distribution.
## Installation
You can install the released version of visualize from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("visualize")
```
And the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("coatless/visualize")
```
## Examples
To use visualize, load the package with:
```{r}
library("visualize")
```
Then, construct a graph by following the `visualize.dist()` pattern. For example,
the normal distribution can be shown with:
```{r visualize-normal}
# Graph a standard normal distribution with a z-score of 1.96
visualize.norm(1.96)
# Change the location of the tail
visualize.norm(1.96, section = "upper")
# Create a bounded range.
visualize.norm(c(-1.96, 1.96), section = "bounded")
# Highlight both tails
visualize.norm(c(-1.96, 1.96), section = "tails")
```
The parameters of the distribution can also be modified. Take for example the
Binomial distribution.
```{r visualize-binomial}
visualize.binom(stat = 9, size = 20, p = 0.5)
# Visualize the binominal distribution with a higher size and lower probability.
visualize.binom(stat = 9, size = 24, p = 0.25)
```
Discrete distributions can also handle a level of strict (`<`, `>`) or equal
to (`<=`, `>=`) inequality.
```{r discrete-inequalities}
# Create a strict inequality (lower < x < higher)
visualize.pois(stat = c(4, 6), lambda = 3.5, section = "bounded",
strict = c(TRUE, TRUE))
# Allow for equality on either side only on the right side of the bounded region.
visualize.pois(stat = c(4, 6), lambda = 3.5, section = "bounded",
strict = c(TRUE, FALSE))
# Allow for equality on either side of the inequality (lower <= x <= higher)
visualize.pois(stat = c(4, 6), lambda = 3.5, section = "bounded",
strict = c(FALSE, FALSE))
```
## Author
James Joseph Balamuta
## Citing the `visualize` package
To ensure future development of the package, please cite `visualize`
package if used during an analysis or simulation study. Citation information
for the package may be acquired by using in *R*:
```{r, eval = FALSE}
citation("visualize")
```
## License
MIT License