View source: R/biodecrypt.optimise.R
biodecrypt.optimise | R Documentation |
The function biodecrypt.optimise analyses the output of biodecrypt.wrap. By default, a combination of MIR^2+NIR+NUR is used as a penalty value for the different combinations of the parameters (providing a higher importance to MIR). The exponents can be changed by the user. Since the method showing the lowest penalty in cross-validation might not necessarily be the optimal value for the final analysis, all the combinations showing a penalty value not higher than a certain threshold compared with the analysis showing the lowest penalty should be considered as similarly good. We provided a value of 10 as a default, representing a variation of about 3 for each addendum of the penalty. The optimal parameters can then be calculated as mean values of distance ratio, alpha and buffer among those used in these cross-validation analyses, weighted by 1/penalty in order to provide an increasing contribution to the solutions showing the lowest penalty values.
biodecrypt.optimise(tab,coef=c(2,1,1), penalty=10)
tab |
A matrix obtained with biodecrypt.wrap. |
coef |
The three exponents to be applied to MIR, NIR and NUR, respectively, to calculate the penalties. |
penalty |
The penalty threshold for inclusion in the calculation. |
ratio |
The optimized ratio value. |
buffer |
The optimized buffer value. |
alpha |
The optimized alpha value. |
MIR |
The weighted average MIR among selected combinations. |
NIR |
The weighted average MIR among selected combinations. |
NUR |
The weighted average MIR among selected combinations. |
Leonardo Dapporto
Platania L. et al. Assigning occurrence data to cryptic taxa improves climatic niche assessments: biodecrypt, a new tool tested on European butterflies. Glocal Ecology and Biogeography (2020).
#See the example provided in biodecrypt.wrap
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