Component functions of a `vgam-class`

object can
be plotted with `plotvgam()`

. These are on the scale of
the linear/additive predictor.

```
plotvgam(x, newdata = NULL, y = NULL, residuals = NULL,
rugplot = TRUE, se = FALSE, scale = 0, raw = TRUE,
offset.arg = 0, deriv.arg = 0, overlay = FALSE,
type.residuals = c("deviance", "working", "pearson", "response"),
plot.arg = TRUE, which.term = NULL, which.cf = NULL,
control = plotvgam.control(...), varxij = 1, ...)
```

newdata

Data frame. May be used to reconstruct the original data set.

y

Unused.

residuals

Logical. If `TRUE`

then residuals are plotted.
See `type.residuals`

rugplot

Logical. If `TRUE`

then a rug plot is plotted at the
foot of each plot. These values are jittered to expose ties.

se

Logical. If `TRUE`

then approximate \(\pm 2\) pointwise
standard error bands are included in the plot.

scale

Numerical. By default, each plot will have its own
y-axis scale. However, by specifying a value, each plot's y-axis
scale will be at least `scale`

wide.

raw

Logical. If `TRUE`

then the smooth functions are those
obtained directly by the algorithm, and are plotted without
having to premultiply with the constraint matrices.
If `FALSE`

then the smooth functions have been premultiply by
the constraint matrices.
The `raw`

argument is directly fed into `predict.vgam()`

.

offset.arg

Numerical vector of length \(r\).
These are added to the component functions. Useful for
separating out the functions when `overlay`

is `TRUE`

.
If `overlay`

is `TRUE`

and there is one covariate then
using the intercept values as the offsets can be a good idea.

deriv.arg

Numerical. The order of the derivative.
Should be assigned an small
integer such as 0, 1, 2. Only applying to `s()`

terms,
it plots the derivative.

overlay

Logical. If `TRUE`

then component functions of the same
covariate are overlaid on each other.
The functions are centered, so `offset.arg`

can be useful
when `overlay`

is `TRUE`

.

type.residuals

if `residuals`

is `TRUE`

then the first
possible value
of this vector, is used to specify the type of residual.

plot.arg

Logical. If `FALSE`

then no plot is produced.

which.term

Character or integer vector containing all terms to be
plotted, e.g., `which.term = c("s(age)", "s(height"))`

or
`which.term = c(2, 5, 9)`

.
By default, all are plotted.

which.cf

An integer-valued vector specifying which linear/additive predictors are to be plotted. The values must be from the set {1,2,…,\(r\)}. By default, all are plotted.

control

Other control parameters. See `plotvgam.control`

.

…

Other arguments that can be fed into
`plotvgam.control`

. This includes line colors,
line widths, line types, etc.

varxij

Positive integer.
Used if `xij`

of `vglm.control`

was used,
this chooses which inner argument the component is plotted against.
This argument is related to `raw = TRUE`

and terms such as
`NS(dum1, dum2)`

and constraint matrices that have more than
one column. The default would plot the smooth against `dum1`

but setting `varxij = 2`

could mean plotting the smooth against
`dum2`

.
See the VGAM website for further information.

The original object, but with the `preplot`

slot of the object
assigned information regarding the plot.

In this help file \(M\) is the number of linear/additive predictors, and \(r\) is the number of columns of the constraint matrix of interest.

Many of `plotvgam()`

's options can be found in
`plotvgam.control`

, e.g., line types, line widths,
colors.

`vgam`

,
`plotvgam.control`

,
`predict.vgam`

,
`plotvglm`

,
`vglm`

.

```
# NOT RUN {
coalminers <- transform(coalminers, Age = (age - 42) / 5)
fit <- vgam(cbind(nBnW, nBW, BnW, BW) ~ s(Age),
binom2.or(zero = NULL), data = coalminers)
# }
# NOT RUN {
par(mfrow = c(1,3))
plot(fit, se = TRUE, ylim = c(-3, 2), las = 1)
plot(fit, se = TRUE, which.cf = 1:2, lcol = "blue", scol = "orange",
ylim = c(-3, 2))
plot(fit, se = TRUE, which.cf = 1:2, lcol = "blue", scol = "orange",
overlay = TRUE)
# }
```

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