---
title: "Bayesian Linear Models for FLUSSHYGIENE"
author: "Carsten Vick"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Bayesian Linear Models for FLUSSHYGIENE}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```
## FLUSSHYGIENE
The work on this package and its functions were mainly done inside the **FLUSSHYGIENE** project at *Kompetenzzentrum Wasser Berlin gGmbH*. Visit [KWB][] and [FLUSSHYGIENE][] for further details.
[KWB]: http://www.kompetenz-wasser.de/en/project/flusshygiene/
[FLUSSHYGIENE]: https://bmbf.nawam-rewam.de/en/projekt/flusshygiene/

Aim of the project is the better understanding of urban river system hygiene. Due to undisinfected treated waste water outlet, combined sewer overflows while heavy rain or flushing of contaminated seperated sewer outlets while light rain, urban rivers tend to be critical water bodies in respect of bathing water quality.

## Bayesian Linear Models
One of the key concepts which has been developed during the project phase is the usage of bayesian linear modelling to predict bathing quality of urban runoff bathing sites. In line with the EU directive it is now possible to predict the distribution of the target value (the *E.Coli* concentration) on a  daily basis. The uncertainty is mirrored in the variance of this distribution and the bathing quality assessment will be derived through the 90th and 95th quantile. That way the decision for a bathing ban is done on a daily basis and can be predicted in the morning when some criterias are met.

A bayesian multivariate linear model is set up via the following regressors:
- the flow rate Q (mean value per day)
- the precepitation amount (daily sum)
- the amount of treated waste water in the runoff (daily sum)


Vignettes are long form documentation commonly included in packages. Because they are part of the distribution of the package, they need to be as compact as possible. The `html_vignette` output type provides a custom style sheet (and tweaks some options) to ensure that the resulting html is as small as possible. The `html_vignette` format:

- Never uses retina figures
- Has a smaller default figure size
- Uses a custom CSS stylesheet instead of the default Twitter Bootstrap style

## Vignette Info

Note the various macros within the `vignette` section of the metadata block above. These are required in order to instruct R how to build the vignette. Note that you should change the `title` field and the `\VignetteIndexEntry` to match the title of your vignette.

## Styles

The `html_vignette` template includes a basic CSS theme. To override this theme you can specify your own CSS in the document metadata as follows:

    output: 
      rmarkdown::html_vignette:
        css: mystyles.css

## Figures

The figure sizes have been customised so that you can easily put two images side-by-side. 

```{r, fig.show='hold'}
plot(1:10)
plot(10:1)
```

You can enable figure captions by `fig_caption: yes` in YAML:

    output:
      rmarkdown::html_vignette:
        fig_caption: yes

Then you can use the chunk option `fig.cap = "Your figure caption."` in **knitr**.

## More Examples

You can write math expressions, e.g. $Y = X\beta + \epsilon$, footnotes^[A footnote here.], and tables, e.g. using `knitr::kable()`.

```{r, echo=FALSE, results='asis'}
knitr::kable(head(mtcars, 10))
```

Also a quote using `>`:

> "He who gives up [code] safety for [code] speed deserves neither."
([via](https://twitter.com/hadleywickham/status/504368538874703872))