These functions are provided for compatibility with older versions only, and may be defunct as soon as the next release.
sparseLTSGrid(x, ...)# S3 method for formula
sparseLTSGrid(formula, data, ...)
# S3 method for default
sparseLTSGrid(x, y, lambda, mode = c("lambda", "fraction"),
...)
a numeric matrix containing the predictor variables.
a formula describing the model.
an optional data frame, list or environment (or object coercible
to a data frame by as.data.frame) containing the variables in
the model. If not found in data, the variables are taken from
environment(formula), typically the environment from which
sparseLTSGrid is called.
a numeric vector containing the response variable.
a numeric vector of non-negative values to be used as penalty parameter.
a character string specifying the type of penalty parameter. If
"lambda", lambda gives the grid of values for the penalty
parameter directly. If "fraction", the smallest value of the penalty
parameter that sets all coefficients to 0 is first estimated based on
bivariate winsorization, then lambda gives the fractions of that
estimate to be used (hence all values of lambda should be in the
interval [0,1] in that case).
additional arguments to be passed down, eventually to
sparseLTS.
sparseLTSGrid is a wrapper function for sparseLTS
that only differs in the default values for the penalty parameter
lambda.