gdm.varcont: Calculates predictor variable (drop) contributions in GDM...
In steppebird/sparsegdm: Package for performing sparse generalized dissimilarity model including tools for gdm
Description
Usage
Arguments
Value
Description
This function calculates predictor variable (drop) contributions in GDM model.
Variable contributions are calculated by the loss in explained deviance in the GDM model, when dropping each individual predictor variable at a time.
It requires a combined site pair dataset ("spData" format) and the optional use of geographical distance as predictor variable in the GDM.
For more details relating to "spData" data format, check gdm package.
Usage
1
gdm.varcont(spData, geo = FALSE)
Arguments
spData
Combined site pair dataset ("spData" format).
geo
Optional use of geographical distance as predictor in GDM model. Set to FALSE per default
Value
Returns variable contribution in percentage
steppebird/sparsegdm documentation built on May 16, 2019, 2:55 a.m.
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Description Usage Arguments Value
Description
This function calculates predictor variable (drop) contributions in GDM model.
Variable contributions are calculated by the loss in explained deviance in the GDM model, when dropping each individual predictor variable at a time.
It requires a combined site pair dataset ("spData" format) and the optional use of geographical distance as predictor variable in the GDM.
For more details relating to "spData" data format, check gdm package.
Usage
1 | gdm.varcont(spData, geo = FALSE)
|
Arguments
spData |
Combined site pair dataset ("spData" format). |
geo |
Optional use of geographical distance as predictor in GDM model. Set to |
Value
Returns variable contribution in percentage
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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