plotCurveEstimate: Function for plotting a fractional polynomial curve estimate
In glmBfp: Bayesian Fractional Polynomials for GLMs

Plot a fractional polynomial curve estimate using samples from a single GLM / Cox model or a model average.

plotCurveEstimate(
  samples,
  termName,
  plevel = 0.95,
  slevel = plevel,
  plot = TRUE,
  rug = FALSE,
  addZeros = FALSE,
  ...
)

`samples`	an object of class `GlmBayesMfpSamples`, produced by `sampleGlm` and `sampleBma`.
`termName`	string denoting an FP term, as written by the `as.data.frame` method
`plevel`	credible level for pointwise HPD, and `NULL` means no pointwise HPD (default: 0.95). The pointwise intervals are plotted in blue color.
`slevel`	credible level for simultaneous credible band (SCB), `NULL` means no SCB (defaults to `plevel`). The simultaneous intervals are plotted in green color.
`plot`	if `FALSE`, only return values needed to produce the plot, but do not plot (default is `TRUE`, so a plot is made)
`rug`	add a rug to the plot? (default: `FALSE`)
`addZeros`	include zero samples for models where the covariate is not included? (default: `FALSE`) If `TRUE`, this changes the interpretation of the samples, and therefore curve estimates based on these samples: it is no longer conditional on inclusion of the covariate, but marginally over all models, also those not including the covariate.
`...`	further arguments for plotting with `matplot`

a list of various plotting information:

`original`	grid on the original covariate scale
`grid`	grid on the transformed scale
`mean`	pointwise mean curve values
`plower`	lower boundaries for pointwise HPD
`pupper`	upper boundaries for pointwise HPD
`slower`	lower boundaries for SCB
`supper`	upper boundaries for SCB
`obsVals`	observed values of the covariate on the original scale
`partialResids`	not implemented: partial residuals
`transform`	vector of shift and scale parameter