Usage
monpol(formula, data, subset, weights, na.action,
degree=3, K, start, trace = FALSE, plot.it = FALSE,
control = monpol.control(),
algorithm = c("Full", "Hawkins", "BCD", "CD1", "CD2"),
ptype = c("Elphinstone", "EHH", "Penttila"),
ctype = c("cge0", "c2"),
model=FALSE, x=FALSE, y=FALSE)Arguments
formula
an object of class "formula" (or one that
can be coerced to that class): a symbolic description of the
model to be fitted. data
an optional data frame, list or environment (or object
coercible by as.data.frame to a data frame) containing
the variables in the model. If not found in data, the
variables subset
an optional vector specifying a subset of observations
to be used in the fitting process.
weights
an optional vector of weights to be used in the fitting
process. Should be NULL or a numeric vector.
na.action
a function which indicates what should happen
when the data contain NAs. The default is set by
the na.action setting of options, and is
degree
a polynomail with highest power equal to degree
will be fitted to the data.
K
a polynomial with highest power $2K+1$ will be fitted to
the data.
start
optional starting value for the iterative fitting.
trace
print out information about the progress of the
interative fitting at the start and then every trace
iterations.
plot.it
plot the data and initial fit, then plot current fit
every plot.it iterations.
control
settings that control the iterative fit; see
monpol.control for details. algorithm
algorithm to be used. It is recommended to use
either Full or Hawkins; see paper in
References for details.
ptype
parameterisation to be used; see paper in
References for details.
ctype
parameterisation to be used; see paper in
References for details.
model, x, y
logicals. If TRUE the corresponding
components of the fit (the model frame, the model matrix, the
response, the QR decomposition) are returned.