rrvglm.extra:"list";
the extra argument on entry to vglm. This
contains any extra information that might be needed
by the family function.
family:"vglmff".
The family function. iter:"numeric".
The number of IRLS iterations used.
predictors:"matrix"
with $M$ columns which holds the $M$ linear predictors.
assign:"list",
from class "vlm".
This named list gives information matching the columns and the
(LM) model matrix terms.
call:"call", from class "vlm".
The matched call.
coefficients:"numeric", from class "vlm".
A named vector of coefficients.
constraints:"list", from
class "vlm".
A named list of constraint matrices used in the fitting.
contrasts:"list", from
class "vlm".
The contrasts used (if any).
control:"list", from class
"vlm".
A list of parameters for controlling the fitting process.
See vglm.control for details.
criterion:"list", from
class "vlm".
List of convergence criterion evaluated at the
final IRLS iteration.
df.residual:"numeric", from class "vlm".
The residual degrees of freedom.
df.total:"numeric",
from class "vlm".
The total degrees of freedom.
dispersion:"numeric",
from class "vlm".
The scaling parameter.
effects:"numeric",
from class "vlm".
The effects.
fitted.values:"matrix", from class "vlm".
The fitted values. This is usually the mean but may be
quantiles, or the location parameter, e.g., in the Cauchy model. misc:"list",
from class "vlm".
A named list to hold miscellaneous parameters.
model:"data.frame",
from class "vlm".
The model frame.
na.action:"list",
from class "vlm".
A list holding information about missing values.
offset:"matrix",
from class "vlm".
If non-zero, a $M$-column matrix of offsets.
post:"list",
from class "vlm"
where post-analysis results may be put.
preplot:"list",
from class "vlm"
used by plotvgam; the plotting parameters
may be put here.
prior.weights:"matrix", from class "vlm"
holding the initially supplied weights.
qr:"list",
from class "vlm".
QR decomposition at the final iteration.
R:"matrix",
from class "vlm".
The R matrix in the QR decomposition used in the fitting.
rank:"integer",
from class "vlm".
Numerical rank of the fitted model.
residuals:"matrix",
from class "vlm".
The working residuals at the final IRLS iteration.
ResSS:"numeric",
from class "vlm".
Residual sum of squares at the final IRLS iteration with
the adjusted dependent vectors and weight matrices.
smart.prediction:"list", from class "vlm".
A list of data-dependent parameters (if any)
that are used by smart prediction.
terms:"list",
from class "vlm".
The terms object used.
weights:"matrix",
from class "vlm".
The weight matrices at the final IRLS iteration.
This is in matrix-band form.
x:"matrix",
from class "vlm".
The model matrix (LM, not VGLM).
xlevels:"list",
from class "vlm".
The levels of the factors, if any, used in fitting.
y:"matrix",
from class "vlm".
The response, in matrix form.
Xm2:"matrix",
from class "vlm".
See vglm-class).
Ym2:"matrix",
from class "vlm".
See vglm-class).
callXm2:"call", from class "vlm".
The matched call for argument form2.
"vglm", directly.
Class "vlm", by class "vglm".signature(x = "rrvglm"): biplot. signature(object = "rrvglm"): more detailed
coefficients giving A,
$\bold{B}1$, C, etc.
signature(object = "rrvglm"):
biplot. signature(x = "rrvglm"):
short summary of the object. signature(object = "rrvglm"):
a more detailed summary of the object. Yee, T. W. and Wild, C. J. (1996) Vector generalized additive models. Journal of the Royal Statistical Society, Series B, Methodological, 58, 481--493.
rrvglm,
lvplot.rrvglm,
vglmff-class.
## Not run: # Rank-1 stereotype model of Anderson (1984)
# pneumo <- transform(pneumo, let = log(exposure.time),
# x3 = runif(nrow(pneumo))) # x3 is unrelated
# fit <- rrvglm(cbind(normal, mild, severe) ~ let + x3,
# multinomial, data = pneumo, Rank = 1)
# Coef(fit)
# ## End(Not run)
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