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, ...)TRUE then residuals are plotted.
  See type.residualsTRUE then a rug plot is plotted at the
  foot of each plot. These values are jittered to expose ties.TRUE then approximate $\pm 2$ pointwise
    standard error bands are included in the plot.scale wide.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 premultoverlay is TRUE.
    If overlay is TRUE and there is one covariate then
  s() terms,
    it plots the derivative.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.residuals is TRUE then the first
      possible value
      of this vector, is used to specify the type of
      residual.FALSE then no plot is produced.which.term = c("s(age)", "s(height")) or
    which.term = c(2, 5, 9).
    By default, all are plotted.plotvgam.control.plotvgam.control. This includes line colors,
  line widths, line types, etc.xij of vglm.control was used,
    this chooses which inner argument the component is plotted against.
    This argument is related to raw = TRUE preplot slot of the object
  assigned information regarding the plot.
  Many of plotvgam()'s options can be found in  
  plotvgam.control, e.g., line types, line widths,
  colors.
Documentation accompanying the 
vgam,
  plotvgam.control,
  predict.vgam,
  vglm.coalminers <- transform(coalminers, Age = (age - 42) / 5)
fit <- vgam(cbind(nBnW, nBW, BnW, BW) ~ s(Age),
            binom2.or(zero = NULL), coalminers)
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)Run the code above in your browser using DataLab