vglm-class {VGAM} | R Documentation |
Vector generalized linear models.
Objects can be created by calls of the form vglm(...)
.
In the following, M is the number of linear predictors.
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.
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
:"numeric"
, 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.
rss
:"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.
Class "vlm"
, directly.
signature(object = "vglm")
:
cumulative distribution function.
Applicable to, e.g., quantile regression and extreme value data models.signature(object = "vglm")
:
Applicable to, e.g., quantile regression.signature(object = "vglm")
:
deviance of the model (where applicable). signature(x = "vglm")
:
diagnostic plots. signature(object = "vglm")
:
extract the linear predictors or
predict the linear 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. Thomas W. Yee
Yee, T. W. and Hastie, T. J. (2003) Reduced-rank vector generalized linear models. Statistical Modelling, 3, 15–41.
Yee, T. W. and Wild, C. J. (1996) Vector generalized additive models. Journal of the Royal Statistical Society, Series B, Methodological, 58, 481–493.
http://www.stat.auckland.ac.nz/~yee
vglm
,
vglmff-class
,
vgam-class
.
# Multinomial logit model data(pneumo) pneumo = transform(pneumo, let=log(exposure.time)) vglm(cbind(normal,mild,severe) ~ let, multinomial, pneumo)