Allows the user to specify a Loess fit in a GAM formula.
USAGE:
lo(..., span=0.5, degree=1)
OPTIONAL ARGUMENTS:
...
the unspecified
... can be a comma-separated list of numeric vectors, numeric matrix, or expressions that evaluate to either of these. If it is a list of vectors, they must all have the same length.
span
the number of observations in a neighborhood. This is the smoothing parameter for a
loess fit.
degree
the degree of local polynomial to be fit; can be
1 or
2.
VALUE:
a numeric matrix is returned. The simplest case is when there is a
single argument to
lo and
degree=1; a one-column matrix is
returned, consisting of a normalized version of the vector. If
degree=2
in this case, a two-column matrix is returned, consisting
of a 2d-degree orthogonal-polynomial basis. Similarly, if there are
two arguments, or the single argument is a two-column matrix, either a
two-column matrix is returned if
degree=1, or a five-column matrix
consisting of powers and products up to degree
2. Any dimensional
argument is allowed, but typically one or two vectors are used in
practice.
The matrix is endowed with a number of attributes;
the matrix itself is used in the construction of the model matrix,
while the attributes are needed for the backfitting
algorithms
all.wam or
lo.wam (weighted additive model).
Local-linear curve or surface fits reproduce linear responses,
while local-quadratic fits reproduce quadratic curves or surfaces.
These parts of the
loess fit are computed exactly together with the
other parametric linear parts of the model.
Note that
lo itself does no smoothing; it simply sets things up for
gam.
SEE ALSO:
,
,
,
,
,
.
EXAMPLES:
y ~ Age + lo(Start, span=.5)
# fit Start using a loess smooth with a span of 0.5.
y ~ lo(Age) + lo(Start, Number)
y ~ lo(Age, 0.5) # the argument name for span is not needed.