data.frameUses fitSpline to fit a spline to a subset of the values
of response and stores the fitted values in data.
The subsets are those values with the same levels combinations
of the factors listed in INDICES and the degrees of
smoothing is controlled by df. The derivatives
of the fitted spline can also be obtained, as can the Relative
Growth Rates (RGR).
By default, smooth.spline will issue an error if there are not
at least four distinct x-values. On the other hand,
fitSpline issues a warning and sets all smoothed values
and derivatives to NA. The handling of missing values in the
observations is controlled via na.x.action and na.y.action.
splitSplines(data, response, x, INDICES, df = NULL, smoothing.scale = "identity",
correctBoundaries = FALSE,
deriv = NULL, suffices.deriv=NULL, RGR=NULL, AGR=NULL, sep=".",
na.x.action="exclude", na.y.action = "exclude", ...)A data.frame containing data to which has been
added a column with the fitted smooth, the name of the column being
response with .smooth appended to it. If deriv is
not NULL, columns containing the values of the derivative(s)
will be added to data; the name each of these columns will
be the value of response with .smooth.dvf appended,
where f is the order of the derivative, or the value of
response with .smooth. and the corresponding
element of suffices.deriv appended. If RGR is not
NULL, the RGR is calculated as the ratio of value of the first
derivative of the fitted spline and the fitted value for the spline.
Any pre-existing smoothed and derivative columns in data will be
replaced. The ordering of the data.frame for the x
values will be preserved as far as is possible; the main difficulty
is with the handling of missing values by the function merge.
Thus, if missing values in x are retained, they will occur at
the bottom of each subset of INDICES and the order will be
problematic when there are missing values in y and
na.y.action is set to omit.
A data.frame containing the column to be smoothed.
A character giving the name of the column in
data that is to be smoothed.
A character giving the name of the column in
data that contains the values of the predictor variable.
A character giving the name(s) of the
factor(s) that define the subsets of response
that are to be smoothed separately. If the columns corresponding to
INDICES are not factor(s) then they will be
coerced to factor(s). The subsets are formed
using split.
A numeric specifying the desired equivalent number of degrees
of freedom of the smooth (trace of the smoother matrix). Lower values
result in more smoothing. If df = NULL, ordinary leave-one-out
cross-validation is used to determine the amount of smooth.
A character giving the scale on which smoothing
is to be performed. The two possibilites are "identity", for directly
smoothing the observed response, and "logarithmic", for scaling the
log-transformed response.
A logical indicating whether the fitted
spline values are to have the method of Huang (2001) applied
to them to correct for estimation bias at the end-points. Note that
deriv must be NULL for correctBoundaries to be
set to TRUE.
A numeric specifying one or more orders of derivatives
that are required.
A character giving the characters to be
appended to the names of the derivatives.
A character giving the character to be appended
to the smoothed response to create the RGR name,
but only when smoothing.scale is identity.
When smoothing.scale is identity:
(i) if RGR is not NULL
deriv must include 1 so that the first derivative is
available for calculating the RGR; (ii) if RGR is NULL,
the RGR is not calculated from the AGR.
When smoothing.scale is logarithmic,
the RGR is the backtransformed first derivative and so, to obtain it, merely
include 1 in deriv and any suffix for it in
suffices.deriv.
A character giving the character to be appended
to the smoothed response to create the AGR name,
but only when smoothing.scale is logarithmic.
When smoothing.scale is logarithmic: (i)
if AGR is not NULL,
deriv must include 1 so that the first derivative is
available for calculating the AGR; (ii) If AGR is NULL,
the AGR is not calculated from the RGR. When smoothing.scale is identity,
the AGR is the first derivative and so, to obtain it, merely
include 1 in deriv and any suffix for it in
suffices.deriv.
A character giving the separator to use when the
levels of INDICES are combined. This is needed to avoid
using a character that occurs in a factor to delimit
levels when the levels of INDICES are combined to identify
subsets.
A character string that specifies the action to
be taken when values of x are NA. The possible
values are fail, exclude or omit.
For exclude and omit, predictions and derivatives
will only be obtained for nonmissing values of x.
The difference between these two codes is that for exclude the returned
data.frame will have as many rows as data, the
missing values have been incorporated.
A character string that specifies the action to
be taken when values of y, or the response, are
NA. The possible values are fail, exclude,
omit, allx, trimx, ltrimx or
rtrimx. For all options, except fail, missing
values in y will be removed before smoothing.
For exclude and omit, predictions
and derivatives will be obtained only for nonmissing values of
x that do not have missing y values. Again, the
difference between these two is that, only for exclude
will the missing values be incorporated into the
returned data.frame. For allx, predictions and
derivatives will be obtained for all nonmissing x.
For trimx, they will be obtained for all nonmissing
x between the first and last nonmissing y values
that have been ordered for x; for ltrimx and
utrimx either the lower or upper missing y
values, respectively, are trimmed.
allows for arguments to be passed to smooth.spline.
Chris Brien
Huang, C. (2001). Boundary corrected cubic smoothing splines. Journal of Statistical Computation and Simulation, 70, 107-121.
fitSpline, smooth.spline,
predict.smooth.spline, splitContGRdiff, split
data(exampleData)
longi.dat <- splitSplines(longi.dat, response="Area", x="xDays",
INDICES = "Snapshot.ID.Tag",
df = 4, deriv=1, suffices.deriv="AGRdv", RGR="RGRdv")
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