Plot GAM smooths.

It plots the smooths from the estimates of a gam or bam object.

plot_smooths(
  model,
  series,
  comparison = NULL,
  facet_terms = NULL,
  conditions = NULL,
  exclude_random = TRUE,
  exclude_terms = NULL,
  series_length = 25,
  split = NULL,
  sep = "\\.",
  transform = NULL,
  ci_z = 1.96,
  time_series
)

Arguments

model	A gam or bam model object.
series	An unquoted expression indicating the model term that defines the series on which smoothing is applied. This is the term that is displayed on the x-axis when plotting.
comparison	An unquoted expression indicating the model term for which the comparison will be plotted.
facet_terms	An unquoted formula with the terms used for faceting.
conditions	A list of quosures with quos specifying the levels to plot from the model terms not among series, comparison, or facet_terms.
exclude_random	Whether to exclude random smooths (the default is TRUE).
exclude_terms	Terms to be excluded from the prediction. Term names should be given as they appear in the model summary (for example, "s(x0,x1)").
series_length	An integer indicating how many values along the time series to use for predicting the outcome term.
split	Columns to separate as a named list.
sep	Separator between columns (default is "\.", which is the default with ). If character, it is interpreted as a regular expression.
transform	Function used to transform the fitted values (useful for getting plots on the response scale).
ci_z	The z-value for calculating the CIs (the default is 1.96 for 95 percent CI).
time_series	Deprecated, use series instead.

Value

A ggplot object.

Examples

library(mgcv)
set.seed(10)
data <- gamSim(4)
#> Factor `by' variable example
model <- gam(y ~ fac + s(x2) + s(x2, by = fac) + s(x0), data = data)

plot_smooths(model, x2, fac)

# alternative model specification
model <- gam(y ~ s(fac, bs = "re") + s(x2) + s(x2, by = fac) + s(x0), data = data)
plot_smooths(model, x2, fac)

# For details, see vignette
if (FALSE) {
vignette("plot-smooths", package = "tidymv")
}