Reduced-rank vector generalized linear models.
Objects can be created by calls to rrvglm
.
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(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 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.
# 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)
# }
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