View source: R/allfunctions_cati.R
Neigbourhood distance metrics | R Documentation |
CVNND : Coefficient of variation of the nearest neigbourhood distance
MNND : Mean of the nearest neigbourhood distance
MinNND : Minimum of the nearest neigbourhood distance
SDNND : Standard deviation of the nearest neigbourhood distance
SDND : Standard deviation of the neigbourhood distance
MND : Mean of the neigbourhood distance
CVNND(traits, div_range = FALSE, na.rm = FALSE, scale.tr = TRUE, method.dist = "euclidian") MNND(traits, div_range = FALSE, na.rm = FALSE, scale.tr = TRUE, method.dist = "euclidian") MinNND(traits, div_range = FALSE, na.rm = FALSE, scale.tr = TRUE, method.dist = "euclidian") SDNND(traits, div_range = FALSE, na.rm = FALSE, scale.tr = TRUE, method.dist = "euclidian") SDND(trait, div_range = FALSE, na.rm = FALSE) MND(trait, div_range = FALSE, na.rm = FALSE)
traits |
Trait vector (uni-trait metric) or traits matrix (Multi-traits metric), traits in column. |
trait |
Trait vector |
div_range |
Does metric need to be divided by the range? Default is no. |
na.rm |
If div_range=TRUE, a logical value indicating whether NA values should be stripped before the computation proceeds. |
scale.tr |
Does traits need to be scale before multi-traits metric calculation? Default is yes. |
method.dist |
Method to calculate the distance in case of multi-traits metric (function dist). Default is euclidian. |
One value corresponding to the metric value.
Adrien Taudiere
Aiba, M., Katabuchi, M., Takafumi, H., Matsuzaki, S.S., Sasaki, T. & Hiura, T. 2013. Robustness of trait distribution metrics for community assembly studies under the uncertainties of assembly processes. Ecology, 94, 2873-2885. Jung, Vincent, Cyrille Violle, Cedric Mondy, Lucien Hoffmann, et Serge Muller. 2010. Intraspecific variability and trait-based community assembly: Intraspecific variability and community assembly. Journal of Ecology 98 (5): 1134-1140.
data(finch.ind) CVNND(traits.finch[,1], na.rm = TRUE) CVNND(traits.finch[,1], div_range = TRUE, na.rm = TRUE) CVNND(traits.finch, na.rm = TRUE) CVNND(traits.finch, scale.tr = FALSE, na.rm = TRUE) SDND(traits.finch[,1], na.rm = TRUE)
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