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Some lines of ideas
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Matthias Grenié committed Dec 4, 2023
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---
title: "fundiversity-5-non-continuous"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{fundiversity-5-non-continuous}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```

```{r setup}
library(fundiversity)
```

fundiversity can only work with trait that are continuous. So what is needed is to transform back the non-continuous traits into continuous measures. There are several ways to do that and it has implications on how the traits influence the functional diversity indices.
fundiversity explicitly excludes functions dealing with transforming non-continuous traits into continuous traits from its features as several other packages exist to work on them. (mFD, ade4, ?)
Here we mention the different questions that have to be answered when doing so by showing one example and one possible workflow to transform non-continuous trait data into continuous data.

How to deal with non-continuous traits?

Different kinds of dissimilarity
Gower's, adapted Gower, dist.ktab()

the nature of distinct type of traits: binary traits by default have greater importance

Cited references
Gower
Pavoine
Maire et al.
De Bello handbook

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