fit.mfp: Function to fit a multivariable fractional polynomial model...
In isglobal-brge/nlOmicAssoc: non-linar omic association

Fits and mfp model for each row in data using mfp package

1 2	fit.mfp(data = data_m, vars_df = vars_df, df = 4L, alpha = 0.05, select = 0.05, cores = 1L, verbose = FALSE, ...)

`vars_df`	data.frame with sampes as rows and variables as columns
`df`	degrees of freedom for mfp, default 4, 1 would be linear
`alpha`	sets the FP selection level for all predictors. Values for individual predictors may be changed via the fp function in the formula.
`select`	select: sets the variable selection level for all predictors. Values for individual predictors may be changed via the fp function in the formula.
`cores`	cores in case of parallelization (no windows)
`verbose`	logical to verbose (comment) the steps of the function, default(FALSE)
`data_m`	`ExpressionSet` or data.frame with samples as columns and observations as rows could be an ExpressionSet(modif!)