createLoessSettings: Create Loess Settings
In rekkasA/SmoothHte: Fit smooth risk-based absolute benefit predictions

Creates the settings for fitting a loess fit.

createLoessSettings(
  weights = numeric(),
  model = FALSE,
  span = 0.75,
  degree = 2,
  parametric = FALSE,
  drop.square = FALSE,
  normalize = TRUE,
  family = "gaussian",
  method = "loess",
  control = stats::loess.control()
)

`weights`	Optional weights for each case.
`model`	Should the model frame be returned?
`span`	The parameter alpha which controls the degree of smoothing.
`degree`	the degree of the polynomials to be used, normally 1 or 2. (Degree 0 is also allowed, but see the ‘Note’.)
`parametric`	Should any terms be fitted globally rather than locally? vector of the same length as the number of predictors.
`drop.square`	For fits with more than one predictor and degree = 2, should the quadratic term be dropped for particular predictors? Terms are specified in the same way as for parametric.
`normalize`	Should the predictors be normalized to a common scale if there is more than one? The normalization used is to set the 10% trimmed standard deviation to one. Set to false for spatial coordinate predictors and others known to be on a common scale.
`family`	If "gaussian" fitting is by least-squares, and if "symmetric" a re-descending M estimator is used with Tukey's biweight function. Can be abbreviated.
`method`	Fit the model or just extract the model frame. Can be abbreviated.
`control`	Control parameters.