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Matthias Grenié
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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} | ||
--- | ||
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```{r, include = FALSE} | ||
knitr::opts_chunk$set( | ||
collapse = TRUE, | ||
comment = "#>" | ||
) | ||
``` | ||
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```{r setup} | ||
library(fundiversity) | ||
``` | ||
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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. | ||
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How to deal with non-continuous traits? | ||
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Different kinds of dissimilarity | ||
Gower's, adapted Gower, dist.ktab() | ||
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the nature of distinct type of traits: binary traits by default have greater importance | ||
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Cited references | ||
Gower | ||
Pavoine | ||
Maire et al. | ||
De Bello handbook |