mixture {BAT} | R Documentation |

## Mixture model.

### Description

Mixture model by Hilario et al. subm.

### Usage

```
mixture(
comm,
tree,
q = 0,
precision = 0.1,
replace = TRUE,
alpha = 0.05,
param = TRUE,
runs = 1000
)
```

### Arguments

`comm` |
A sites x species matrix, with abundance data. |

`tree` |
A phylo or hclust object (used only for PD or FD) or alternatively a species x traits matrix or data.frame to build a functional tree. Will only be used if q = 0, in which case phylogenetic or functional richness are calculated instead of species richness. |

`q` |
Hill number order: q(0) = species richness, q(1) ~ Shannon diversity, q(2) ~ Simpson diversity. |

`precision` |
Precision of the proportion of each habitat type to be tested. |

`replace` |
Boolean indicating whether simulations should be with or without (default) replacement. |

`alpha` |
alpha value for significance level. |

`param` |
Value is calculated with parametric or non-parametric method. The later is preferable when distribution of estimated values is not normally distributed. |

`runs` |
Number of runs for the bootstrap providing confidence limits. |

### Details

A tool to assess biodiversity in landscapes containing varying proportions of n environments.

### Value

A matrix with expected diversity at each proportion of different habitats in a landscape.

### Author(s)

Renato Hilario & Pedro Cardoso

### References

Chao et al. (2019) Proportional mixture of two rarefaction/extrapolation curves to forecast biodiversity changes under landscape transformation. Ecology Letters, 22: 1913-1922. https://doi.org/10.1111/ele.13322

Hilario et al. (subm.) Function ‘mixture’: A new tool to quantify biodiversity change under landscape transformation.

### Examples

```
comm <- matrix(c(20,20,20,20,20,9,1,0,0,0,1,1,1,1,1), nrow = 3, ncol = 5, byrow = TRUE)
tree = hclust(dist(1:5))
hill(comm)
alpha(comm, tree)
mixture(comm, runs = 10)
mixture(comm, tree, replace = TRUE, runs = 10)
```

*BAT*version 2.9.6 Index]