# tSamp: Trait Values Sampling In TPD: Methods for Measuring Functional Diversity Based on Trait Probability Density

## Description

`tSamp` samples (with replacement) trait values from populations, species or communities. The probability of sampling each trait –or combination of traits in multidimensional cases– is proportional to the value of TPDs or TPDc for the corresponding cell (the trait space is divided in a grid composed of cells, see `TPDs` for further information).

## Usage

 `1` ```tSamp(TPDc = NULL, TPDs = NULL, size = 1) ```

## Arguments

 `TPDc` An object of class "TPDcomm", generated with the `TPDc` function, containing the TPDc of the considered communities. `TPDs` An object of class "TPDsp", generated with the `TPDs` function, containing the TPDs of the considered populations or species. `size` Non-negative integer giving the number of observations to choose. Defaults to 1.

## Value

`tSamp` returns a list containing sampled trait values for each community of TPDc or species/populations from TPDs.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```# 1. Compute the TPDs of three different species traits_iris <- iris[, c("Sepal.Length", "Sepal.Width")] sp_iris <- iris\$Species example_TPDs <- TPDs(species = sp_iris, traits = traits_iris) #2. Three different communities with different abundances of each species example_abundances <- matrix(c(c(0.5, 0.3, 0.2, 0.1, 0.8, 0.1, 0.5, 0, 0.5)), #I. virg. dominates; setosa absent ncol = 3, byrow = TRUE, dimnames = list(paste0("Comm.",1:3), unique(iris\$Species))) example_TPDc <- TPDc (TPDs = example_TPDs, sampUnit = example_abundances) #3. Sample 1,000 trait values from each species and community example_sampling <- tSamp(TPDc = example_TPDc, TPDs = example_TPDs, size = 1000) ```

TPD documentation built on July 3, 2019, 1:05 a.m.