View source: R/bm_MakeFormula.R
| bm_MakeFormula | R Documentation |
This internal biomod2 function allows the user to create easily a standardized formula that can be used later by statistical models.
bm_MakeFormula(
resp.name,
expl.var,
type = "simple",
interaction.level = 0,
k = NULL
)
resp.name |
a |
expl.var |
a |
type |
a |
interaction.level |
an |
k |
(optional, default |
It is advised to give only a subset of expl.var table to avoid useless memory consuming.
If some explanatory variables are factorial, expl.var must be a data.frame
whose corresponding columns are defined as factor.
A formula class object that can be directly given to most of
R statistical models.
Damien Georges
formula, s, s,
bm_ModelingOptions, bm_Tuning,
bm_RunModelsLoop
Other Secundary functions:
bm_BinaryTransformation(),
bm_CrossValidation(),
bm_FindOptimStat(),
bm_ModelingOptions(),
bm_PlotEvalBoxplot(),
bm_PlotEvalMean(),
bm_PlotRangeSize(),
bm_PlotResponseCurves(),
bm_PlotVarImpBoxplot(),
bm_PseudoAbsences(),
bm_RunModelsLoop(),
bm_SRE(),
bm_SampleBinaryVector(),
bm_SampleFactorLevels(),
bm_Tuning(),
bm_VariablesImportance()
## Create simple simulated data
myResp.s <- sample(c(0, 1), 20, replace = TRUE)
myExpl.s <- data.frame(var1 = sample(c(0, 1), 100, replace = TRUE),
var2 = rnorm(100),
var3 = 1:100)
## Generate automatic formula
bm_MakeFormula(resp.name = 'myResp.s',
expl.var = head(myExpl.s),
type = 'quadratic',
interaction.level = 0)
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