Smooths and confidence intervals.

Source: R/plotting.R

It provides a `geom` for plotting GAM smooths with confidence intervals from the output of predict_gam. It inherits the following aesthetics from a call to ggplot:

  • The term defining the x-axis.

  • The fitted values (the fit column in the tibble returned by predict_gam).

  • The standard error of the fit (the se.fit column in the tibble returned by predict_gam).

geom_smooth_ci(group = NULL, ci_z = 1.96, ci_alpha = 0.1, data = NULL, ...)

Arguments

group

The optional grouping factor.
ci_z

The z-value for calculating the CIs (the default is 1.96 for 95 percent CI).
ci_alpha

Transparency value of CIs (the default is 0.1).
data

The data to be displayed in this layer. If NULL, it is inherited.
...

Arguments passed to geom_path().

Examples

library(mgcv)

#> Loading required package: nlme
#> 
#> Attaching package: ‘nlme’
#> The following object is masked from ‘package:dplyr’:
#> 
#>     collapse
#> This is mgcv 1.8-34. For overview type 'help("mgcv-package")'.
library(ggplot2)
set.seed(10)
data <- gamSim(4)

#> Factor `by' variable example
model <- gam(y ~ fac + s(x2) + s(x2, by = fac), data = data)

# get predictions
p <- predict_gam(model)

# plot smooths and confidence intervals
ggplot(p, aes(x2, fit)) + geom_smooth_ci(fac)