createLocfitSettings: Create Locfit settings
In rekkasA/SmoothHte: Fit smooth risk-based absolute benefit predictions

Create the settings for fitting a local likelihood approach for smooth risk-based prediction of absolute benefit.

createLocfitSettings(
  kern = "tricube",
  kt = "sph",
  family = "binomial",
  link = "default",
  maxk = 100,
  mint = 20,
  maxit = 20,
  debug = 0
)

`kern`	Weight function, default = "tcub". Other choices are "rect", "trwt", "tria", "epan", "bisq" and "gauss". Choices may be restricted when derivatives are required; e.g. for confidence bands and some bandwidth selectors.
`kt`	Kernel type, "sph" (default); "prod". In multivariate problems, "prod" uses a simplified product model which speeds up computations.
`family`	Local likelihood family; "gaussian"; "binomial"; "poisson"; "gamma" and "geom". Density and rate estimation families are "dens", "rate" and "hazard" (hazard rate). If the family is preceded by a 'q' (for example, family="qbinomial"), quasi-likelihood variance estimates are used. Otherwise, the residual variance (rv) is fixed at 1. The default family is "qgauss" if a response y is provided; "density" if no response is provided.
`link`	Link function for local likelihood fitting. Depending on the family, choices may be "ident", "log", "logit", "inverse", "sqrt" and "arcsin".
`maxk`	Controls space assignment for evaluation structures. For the adaptive evaluation structures, it is impossible to be sure in advance how many vertices will be generated. If you get warnings about ‘Insufficient vertex space’, Locfit's default assigment can be increased by increasing maxk. The default is maxk=100.
`mint`	Points for numerical integration rules. Default 20.
`maxit`	Maximum iterations for local likelihood estimation. Default 20.
`debug`	If > 0; prints out some debugging information