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, ...)
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` |