run_gams: Run GAM with given predictors & response variable on given...
In DanielReedOcean/ACCASPR: For Fitting Generalised Additive Models to Fish Stock Metrics
Description
Usage
Arguments
Value
Description
Generalised additive models describing the response variable, response, are constructed using all
possible combinations of the given predictors, preds. These models are fit using the given data frame,
data, and contain up to and including max_n terms. These are smoothed terms with k knots.
Usage
1
Arguments
preds
Names of the predictors (vector of strings)
response
Name of response variable (string)
kval
Number of knots in the smoothers (numeric)
max_n
Maximum number of terms in each GAM (numeric)
data
Data set that includes the predictors and response variable (data frame)
Value
List of gams
DanielReedOcean/ACCASPR documentation built on Aug. 22, 2019, 3:34 a.m.
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Description Usage Arguments Value
Description
Generalised additive models describing the response variable, response, are constructed using all
possible combinations of the given predictors, preds. These models are fit using the given data frame,
data, and contain up to and including max_n terms. These are smoothed terms with k knots.
Usage
1 |
Arguments
preds |
Names of the predictors (vector of strings) |
response |
Name of response variable (string) |
kval |
Number of knots in the smoothers (numeric) |
max_n |
Maximum number of terms in each GAM (numeric) |
data |
Data set that includes the predictors and response variable (data frame) |
Value
List of gams
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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