GAM model is fitted for each row in data using mboost package
1 2 | fit.gamboost(data = data_m, vars_df = vars_df, df = 3, cores = 1L,
verbose = FALSE, ...)
|
data |
|
vars_df |
data.frame with sampes as rows and variables as columns |
df |
degrees of freedom to apply to model |
cores |
cores in case of parallelization (no windows) |
verbose |
logical to verbose (comment) the steps of the function, default(FALSE) |
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