The variable plotted on the y-axis is the first column with residual error that is available in the predicted result. You can easily influence this by providing a `newdata` argument.

# S3 method for tdmorefit
autolayer(
  x,
  color = "tomato1",
  fill = color,
  alpha = 0.2,
  se.fit = T,
  level = 0.95,
  ...,
  na.rm = TRUE
)

# S3 method for tdmore
autoplot(x, regimen = NULL, covariates = NULL, newdata = NULL, ...)

Arguments

x

a tdmore object

color

color to use for the line

fill

fill color to use for the ribbon

alpha

alpha level for the ribbon

se.fit

plot a confidence band around the prediction?

level

level for the confidence band

...

extra arguments

na.rm

should NA be removed

regimen

the regimen

covariates

the covariates

newdata

passed to `predict`