README.Rmd

---
output: rmarkdown::github_document
editor_options: 
  chunk_output_type: inline
---
```{r pkg-knitr-opts, include=FALSE}
knitr::opts_chunk$set(
  collapse = TRUE, fig.retina = 2, message = FALSE, warning = FALSE
)
options(width=120)
```

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# gglogspline

A 'ggplot2' Extension for Visualizing Density, Distribution, Hazard, or Survival Functions using the 'logspline' Package

## Description

Methods are provided to plot a logspline density, distribution function, hazard function or survival function from a logspline density

## What's Inside The Tin

The following functions are implemented:

- `stat_logspline`:	Computes logspline density (+ counts estimate), probability, survival & hazard

## Installation

```{r install-ex, eval=FALSE}
install("gglogspline", repos = "https://cinc.rud.is")
# or
devtools::install_git("https://git.sr.ht/~hrbrmstr/gglogspline.git")
# or
devtools::install_git("https://git.rud.is/hrbrmstr/gglogspline.git")
# or
devtools::install_gitlab("hrbrmstr/gglogspline")
# or
devtools::install_bitbucket("hrbrmstr/gglogspline")
# or
devtools::install_github("hrbrmstr/gglogspline")
```

## Usage

```{r lib-ex}
library(gglogspline)
library(ggplot2)

# current version
packageVersion("gglogspline")

```

```{r}
set.seed(1)
data.frame(
  val = rnorm(100)
) -> xdf

ggplot(xdf) + 
  stat_logspline(aes(val))

ggplot(xdf) + 
  stat_logspline(aes(val, y = stat(count))) +
  labs(title = "logspline (count)")

ggplot(xdf) +
  stat_logspline(aes(val, y = stat(probs))) +
  labs(title = "logspline (probability function)")

ggplot(xdf) +
  stat_logspline(aes(val, y = stat(survival))) +
  labs(title = "logspline (survival function)")

ggplot(xdf) +
  stat_logspline(aes(val, y = stat(hazard))) +
  labs(title = "logspline (hazard function)")
```

## gglogspline Metrics

```{r cloc, echo=FALSE}
cloc::cloc_pkg_md()
```

## Code of Conduct

Please note that this project is released with a [Contributor Code of Conduct](CONDUCT.md). 
By participating in this project you agree to abide by its terms.