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, ...)Data frame. May be used to reconstruct the original data set.
Unused.
Logical. If TRUE then residuals are plotted.
  See type.residuals
Logical. If TRUE then a rug plot is plotted at the
  foot of each plot. These values are jittered to expose ties.
Logical. If TRUE then approximate \(\pm 2\) pointwise
  standard error bands are included in the plot.
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.
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().
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.
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.
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.
if residuals is TRUE then the first
  possible value
  of this vector, is used to specify the type of residual.
Logical. If FALSE then no plot is produced.
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.
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.
Other control parameters. See plotvgam.control.
Other arguments that can be fed into
  plotvgam.control. This includes line colors,
  line widths, line types, etc.
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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