Description Usage Arguments Value
Troll Model Validation : functional diversity with Leinster-Cobbold Entropy using resampling and "rolled under the armpits" Goodness of Fit statistics.
1 2 3 | fonctional_div_species(data, trollsim, speciescol, speciestraits, LMA = "LMA",
N = "N", P = "P", wsg = "wsg", ah = "ah", hmax = "hmax",
dmax = "dmax", n_resample = 10000, path, nameplot)
|
data |
Data.frame ; An inventory which contains at least species name. |
trollsim |
Data.frame (yet not adapted to trollsim S4 objects)with species name Diameters should correspon in terms of lower bound (generally 10cm) between field data and trollsim : pre-filtering is recommended to make consistent comparisons. |
speciescol |
Character indicating the name of the species identity column |
speciestraits |
Data.frame the contains species name and the 7 traits (species-specific mean values) |
LMA |
Character indicating the name of the LMA species means column |
N |
Character indicating the name of the N species means column |
P |
Character indicating the name of the P species means column |
wsg |
Character indicating the name of the wsg species means column |
ah |
Character indicating the name of the ah species means column |
hmax |
Character indicating the name of the hmax species means column |
dmax |
Character indicating the name of the dmax species means column |
n_resample |
Integer ; the number of times you wish to resample to infer sampling effects. |
path |
Character ; The path to the directory you want to save the graphical outputs into. |
nameplot |
Character ; the name of your plot (used to generate outputs' filenames) |
A matrix of computed distances of the resampled Leinster-Cobbold Entropy profiles (LCEP) and the original dataset's LCEP using two distance statistics : (is the first one alright ??) dist = sqrt(sum((LC_data - LC_sample)^2)/nrow(LC_data)) and chi =(sum((LC_sample-LC_data)^2)/LC_data)
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