compare_smooths: Compare smooths across models

In gratia: Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'

Compare smooths across models

Description

Compare smooths across models

Usage

compare_smooths(
  model,
  ...,
  smooths = NULL,
  n = 100,
  data = NULL,
  unconditional = FALSE,
  overall_uncertainty = TRUE
)

Arguments

model	Primary model for comparison.
...	Additional models to compare smooths against those of model.
smooths	character; vector of smooths to compare. If not specified comparisons will be performed for smooths common to all models supplied.
n	numeric; the number of points over the range of the covariate at which to evaluate the smooth.
data	a data frame of covariate values at which to evaluate the smooth.
unconditional	logical; should confidence intervals include the uncertainty due to smoothness selection? If TRUE, the corrected Bayesian covariance matrix will be used.
overall_uncertainty	logical; should the uncertainty in the model constant term be included in the standard error of the evaluate values of the smooth?

Examples

load_mgcv()
dat <- data_sim("eg1", seed = 2)

## models to compare smooths across - artificially create differences
m1 <- gam(y ~ s(x0, k = 5) + s(x1, k = 5) + s(x2, k = 5) + s(x3, k = 5),
          data = dat, method = "REML")
m2 <- gam(y ~ s(x0, bs = 'ts') + s(x1, bs = 'ts') + s(x2, bs = 'ts') +
          s(x3, bs = 'ts'), data = dat, method = "REML")

## build comparisons
comp <- compare_smooths(m1, m2)
comp
## notice that the result is a nested tibble

draw(comp)

gratia documentation built on Feb. 16, 2023, 10:40 p.m.