## parameterpal

Rather than knowing intrinsically what parameters are required for a distribution, scientists tend to have a sense of what value they expect a measure to take, how many observations should fall within a certain distance of that value.

For the normal distribution, this is straightforward, as the parameters reflect the expected value and variance. However, for the beta distribution, the parameters are not so readily interpretable.

parameterpal:: provides a means of obtaining the parameters required for the beta distribution from interpretable conditions.

## installation

```
devtools::install_github("softloud/parameterpal", build_vignettes = TRUE)
```

## launch tutorial

After installation, the `parameterpal::`

tutorial will be available in

the Tutorial pane of Rstudio.

```
# executing this code will launch the tutorial in your browser
learnr::run_tutorial("ppalhelp", package = "parameterpal")
```

## documentation

See this package’s

`pkgdown::`

-generated

site for more information.

## intended user

This package was developed for a friend and collaborator, computational

ecologist Dr Matthew Grainger, who

previously used browser-based tools to obtain beta parameters to inform

his rstats workflow. I hope he finds this package a useful augment to

his codeflow.

# vignette

See `vignette("betapal")`

for ~~more information~~ the same information,

but from the handy ease of your Rstudio Viewer pane.

Full disclosure, I need to update it after I fully understand this

gist I

was provided with after posting the first version of this software to

twitter. Open science at its best. Blogpost incoming on open science and

why it’s good to share bad math and beta research code. So cool I’ve

ended up with a better, more mathematically correct solution after

posting it.

# other distributions

No reason the same math can’t be applied to other distributions. Open an

issue if you’d like me to provide parameters from interpretable

conditions for another distribution.