View source: R/smooth.basis.sparse.R
smooth.basis.sparse | R Documentation |
Makes it possible to perform smoothing with smooth.basis
when the
data has NAs.
smooth.basis.sparse(argvals, y, fdParobj, fdnames=NULL, covariates=NULL,
method="chol", dfscale=1 )
argvals |
a set of argument values corresponding to the observations in array
|
y |
an set of values of curves at discrete sampling points or
argument values. If the set is supplied as a matrix object, the rows must
correspond to argument values and columns to replications, and it will be
assumed that there is only one variable per observation. If
|
fdParobj |
a functional parameter object, a functional data object or a
functional basis object. In the simplest case, |
fdnames |
a list of length 3 containing character vectors of names for the following:
|
covariates |
The observed values in |
method |
by default the function uses the usual textbook equations for computing
the coefficients of the basis function expansions. But, as in regression
analysis, a price is paid in terms of rounding error for such
computations since they involved cross-products of basis function
values. Optionally, if |
dfscale |
the generalized cross-validation or "gcv" criterion that is often used
to determine the size of the smoothing parameter involves the
subtraction of an measue of degrees of freedom from |
an object of class fd
.
smooth.basis
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