Functions from gamlss/gamlss.add with bugs fixed

The control for ga(). From gamlss.add::ga.control() and gamlss::gam().

Usage

ga.control(
  offset = NULL,
  method = "REML",
  optimizer = c("outer", "newton"),
  control = list(),
  scale = 0,
  select = FALSE,
  knots = NULL,
  sp = NULL,
  min.sp = NULL,
  H = NULL,
  gamma = 1,
  paraPen = NULL,
  in.out = NULL,
  drop.unused.levels = TRUE,
  drop.intercept = NULL,
  discrete = FALSE,
  ...
)

Arguments

offset: The offset in the formula.
method: The smoothing parameter estimation method.
optimizer: An array specifying the numerical optimization method to use to optimize the smoothing parameter estimation criterion (given by method)
control: A list of fit control parameters to replace defaults returned by gam.control.
scale: If this is positive then it is taken as the known scale parameter. Negative signals that the scale parameter is unknown. 0 signals that the scale parameter is 1 for Poisson and binomial and unknown otherwise.
select: If this is TRUE then gam() can add an extra penalty to each term so that it can be penalized to zero.
knots: This is an optional list containing user specified knot values to be used for basis construction.
sp: A vector of smoothing parameters can be provided here.
min.sp: Lower bounds can be supplied for the smoothing parameters.
H: A user supplied fixed quadratic penalty on the parameters of the GAM can be supplied, with this as its coefficient matrix.
gamma: Increase this beyond 1 to produce smoother models.
paraPen: Optional list specifying any penalties to be applied to parametric model terms.
in.out: Optional list for initializing outer iteration.
drop.unused.levels: By default unused levels are dropped from factors before fitting. For some smooths involving factor variables you might want to turn this off.
drop.intercept: Set to TRUE to force the model to really not have the a constant in the parametric model part, even with factor variables present. Can be vector when formula is a list.
discrete: Experimental option for setting up models for use with discrete methods employed in bam.
...: Other arguments

Value

A control object