Vector generalized additive models.
Objects can be created by calls of the form vgam(...).
nl.chisq:Object of class "numeric".
Nonlinear chi-squared values.
nl.df:Object of class "numeric".
Nonlinear chi-squared degrees of freedom values.
spar:Object of class "numeric"
containing the (scaled) smoothing parameters.
s.xargument:Object of class "character"
holding the variable name of any s() terms.
var:Object of class "matrix" holding
approximate pointwise standard error information.
Bspline:Object of class "list"
holding the scaled (internal and boundary) knots, and the
fitted B-spline coefficients. These are used
for prediction.
extra:Object of class "list";
the extra argument on entry to vglm. This
contains any extra information that might be needed
by the family function.
family:Object of class "vglmff".
The family function.
iter:Object of class "numeric".
The number of IRLS iterations used.
predictors:Object of class "matrix"
with \(M\) columns which holds the \(M\) linear predictors.
assign:Object of class "list",
from class "vlm".
This named list gives information matching the columns and the
(LM) model matrix terms.
call:Object of class "call", from class
"vlm".
The matched call.
coefficients:Object of class
"numeric", from class "vlm".
A named vector of coefficients.
constraints:Object of class "list", from
class "vlm".
A named list of constraint matrices used in the fitting.
contrasts:Object of class "list", from
class "vlm".
The contrasts used (if any).
control:Object of class "list", from class
"vlm".
A list of parameters for controlling the fitting process.
See vglm.control for details.
criterion:Object of class "list", from
class "vlm".
List of convergence criterion evaluated at the
final IRLS iteration.
df.residual:Object of class
"numeric", from class "vlm".
The residual degrees of freedom.
df.total:Object of class "numeric",
from class "vlm".
The total degrees of freedom.
dispersion:Object of class "numeric",
from class "vlm".
The scaling parameter.
effects:Object of class "numeric",
from class "vlm".
The effects.
fitted.values:Object of class
"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:Object of class "list",
from class "vlm".
A named list to hold miscellaneous parameters.
model:Object of class "data.frame",
from class "vlm".
The model frame.
na.action:Object of class "list",
from class "vlm".
A list holding information about missing values.
offset:Object of class "matrix",
from class "vlm".
If non-zero, a \(M\)-column matrix of offsets.
post:Object of class "list",
from class "vlm"
where post-analysis results may be put.
preplot:Object of class "list",
from class "vlm"
used by plotvgam; the plotting parameters
may be put here.
prior.weights:Object of class
"matrix", from class "vlm"
holding the initially supplied weights.
qr:Object of class "list",
from class "vlm".
QR decomposition at the final iteration.
R:Object of class "matrix",
from class "vlm".
The R matrix in the QR decomposition used in the fitting.
rank:Object of class "integer",
from class "vlm".
Numerical rank of the fitted model.
residuals:Object of class "matrix",
from class "vlm".
The working residuals at the final IRLS iteration.
ResSS:Object of class "numeric",
from class "vlm".
Residual sum of squares at the final IRLS iteration with
the adjusted dependent vectors and weight matrices.
smart.prediction:Object of class
"list", from class "vlm".
A list of data-dependent parameters (if any)
that are used by smart prediction.
terms:Object of class "list",
from class "vlm".
The terms object used.
weights:Object of class "matrix",
from class "vlm".
The weight matrices at the final IRLS iteration.
This is in matrix-band form.
x:Object of class "matrix",
from class "vlm".
The model matrix (LM, not VGLM).
xlevels:Object of class "list",
from class "vlm".
The levels of the factors, if any, used in fitting.
y:Object of class "matrix",
from class "vlm".
The response, in matrix form.
Xm2:Object of class "matrix",
from class "vlm".
See vglm-class).
Ym2:Object of class "matrix",
from class "vlm".
See vglm-class).
callXm2:Object of class "call", from class "vlm".
The matched call for argument form2.
Class "vglm", directly.
Class "vlm", by class "vglm".
signature(object = "vglm"):
cumulative distribution function.
Useful for quantile regression and extreme value data models.
signature(object = "vglm"):
density plot.
Useful for quantile regression models.
signature(object = "vglm"):
deviance of the model (where applicable).
signature(x = "vglm"):
diagnostic plots.
signature(object = "vglm"):
extract the additive predictors or
predict the additive predictors at a new data frame.
signature(x = "vglm"):
short summary of the object.
signature(object = "vglm"):
quantile plot (only applicable to some models).
signature(object = "vglm"):
residuals. There are various types of these.
signature(object = "vglm"):
residuals. Shorthand for resid.
signature(object = "vglm"): return level plot.
Useful for extreme value data models.
signature(object = "vglm"):
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.
# NOT RUN {
# Fit a nonparametric proportional odds model
pneumo <- transform(pneumo, let = log(exposure.time))
vgam(cbind(normal, mild, severe) ~ s(let),
cumulative(parallel = TRUE), data = pneumo)
# }
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