Arguments
coefficients
the coefficients of the linear predictor, which multiply the
columns of the model matrix. The names of the coefficients are
the names of the single-degree-of-freedom effects (the columns
of the model matrix). If the model is over-de
dispersion
the (estimated or known) value of the scale parameter.
fixed
a logical value. If TRUE, the scale parameter is fixed.
residuals
the response residuals from the fit. If weights were used, they
are not taken into account. If you need other kinds of
residuals, use the residuals.rsm function. fitted.values
the fitted values from the fit. If weights were used, the fitted
values are not adjusted for the weights.
loglik
the log likelihood from the fit.
q1
the value of the first derivative of minus the log density for
each observation.
q2
the value of the second derivative of minus the log density for
each observation.
rank
the computed rank (number of linearly independent columns in the
model matrix).
R
the unscaled observed information matrix.
score.dispersion
a list containing the value of the objective function, its gradient
and the convergence diagnostic, that result from estimating the
scale parameter.
iter
the number of IRLS iterations used to compute the
estimates. weights
the (optional) weights used for the fit.
assign
the list of assignments of coefficients (and effects) to the terms
in the model. The names of this list are the names of the terms.
The ith element of the list is the vector saying which
coefficients correspond to the i
df.residuals
the number of degrees of freedom for residuals.
family
the entire family.rsm object used.
user.def
a logical value. If TRUE, the error distribution is
user-defined.
dist
a character string representing the name of the error
distribution.
formula
the model formula.
data
the data frame in which to interpret the variables occurring in
the model formula, or in the subset and the weights
arguments to rsm.
terms
an object of mode expression and class term
summarizing the formula.
contrasts
a list containing sufficient information to construct the contrasts
used to fit any factors occurring in the model. The list contains
entries that are either matrices or character vectors. When a
factor is coded by contrasts, the corr
control
a list of iteration and algorithmic constants used in rsm
to fit the model.
call
an image of the call that produced the object, but with the
arguments all named and with the actual formula included as the
formula argument.
y
optionally the response, if y = TRUE in the original
rsm call.
x
optionally the model matrix, if x = TRUE in the original
rsm call.
model
optionally the model frame, if model = TRUE in the original
rsm call.