Compare smooths across models

Usage

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

Arguments

model: Primary model for comparison.
...: Additional models to compare smooths against those of model.
select: character; select which smooths to compare. The default (NULL) means all smooths in model will be compared. Numeric select indexes the smooths in the order they are specified in the formula and stored in model. Character select matches the labels for smooths as shown for example in the output from summary(object). Logical select operates as per numeric select in the order that smooths are stored.
smooths: Use select instead.
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?
partial_match: logical; should smooths be selected by partial matches with select? If TRUE, select can only be a single string to match against.

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
#> # A tibble: 8 x 5
#>   .model .smooth .type         .by   data              
#>   <chr>  <chr>   <chr>         <chr> <list>            
#> 1 m1     s(x0)   TPRS          NA    <tibble [100 x 3]>
#> 2 m2     s(x0)   TPRS (shrink) NA    <tibble [100 x 3]>
#> 3 m1     s(x1)   TPRS          NA    <tibble [100 x 3]>
#> 4 m2     s(x1)   TPRS (shrink) NA    <tibble [100 x 3]>
#> 5 m1     s(x2)   TPRS          NA    <tibble [100 x 3]>
#> 6 m2     s(x2)   TPRS (shrink) NA    <tibble [100 x 3]>
#> 7 m1     s(x3)   TPRS          NA    <tibble [100 x 3]>
#> 8 m2     s(x3)   TPRS (shrink) NA    <tibble [100 x 3]>
## notice that the result is a nested tibble

draw(comp)