vgam
are set using this function.vgam.control(all.knots = FALSE, bf.epsilon = 1e-07, bf.maxit = 30,
checkwz=TRUE, criterion = names(.min.criterion.VGAM),
epsilon = 1e-07, maxit = 30, na.action = na.fail,
nk = NULL, save.weight = FALSE, se.fit = TRUE,
trace = FALSE, wzepsilon = .Machine$double.eps^0.75,
...)
all.knots=TRUE
for
$n \leq 40$, and
for $n > 40$,
the number of knots is approximately
$40 + (n-40)^{0.25}$.
This increaswzepsilon
. If not,
any values less than wzepsilon
are replaced wit.min.criterion.VGAM
, but
most family functions only implement a few of these.criterion
values are within
epsilon
of each other.gam
function, vgam
cannot handle
NA
s when smoothing.s
terms
in the formula.
Recycling is used if necessary.
The $i$th value is the number of B-spline coefficients to be
estimweights
slot
of a "vglm"
object will be saved on the object.
If not, it will be reconstructed when needed, e.g., summary
.TRUE
, then these can be plotted with plot(..., se = TRUE)
.control
slot of vgam
objects.vgam.fit
and you will have to look at that
to understand the full details. Many of the control
parameters are used in a similar manner by vglm.fit
(vglm
) because the algorithm (IRLS) is
very similar.
Setting save.weight=FALSE
is useful for some
models because the weights
slot of the object is
often the largest and so less memory is used to store the
object. However, for some save.weight=TRUE
because
the weights
slot cannot be reconstructed later.
vgam
,
vglm.control
,
vsmooth.spline
,
vglm
.pneumo = transform(pneumo, let = log(exposure.time))
vgam(cbind(normal, mild, severe) ~ s(let, df = 2), multinomial,
data = pneumo, trace = TRUE, eps = 1e-4, maxit = 10)
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