Glance at many fitted model objects

glances() repeatedly calls glance() on several fitted model objects and binds the output together, sorted by a column of interest.

# S3 method for ssn_lm
glances(object, ..., sort_by = "AICc", decreasing = FALSE)

# S3 method for ssn_glm
glances(object, ..., sort_by = "AICc", decreasing = FALSE)

Arguments

object

Fitted model object from ssn_lm() or ssn_glm().

...

Additional fitted model objects from ssn_lm() or ssn_glm().

sort_by

Sort by a glance statistic (i.e., the name of a column output from glance() or the order of model input (sort_by = "order"). The default is "AICc".

decreasing

Should sort_by be decreasing or not? The default is FALSE.

Value

A tibble where each row represents the output of glance() for each fitted model object.

Examples

# Copy the mf04p .ssn data to a local directory and read it into R
# When modeling with your .ssn object, you will load it using the relevant
# path to the .ssn data on your machine
copy_lsn_to_temp()
temp_path <- paste0(tempdir(), "/MiddleFork04.ssn")
mf04p <- ssn_import(temp_path, overwrite = TRUE)

# tailup only
ssn_mod1 <- ssn_lm(
  formula = Summer_mn ~ ELEV_DEM,
  ssn.object = mf04p,
  tailup_type = "exponential",
  additive = "afvArea"
)
# taildown only
ssn_mod2 <- ssn_lm(
  formula = Summer_mn ~ ELEV_DEM,
  ssn.object = mf04p,
  taildown_type = "exponential"
)
glances(ssn_mod1, ssn_mod2)
#> # A tibble: 2 × 10
#>   model        n     p  npar value   AIC  AICc logLik deviance pseudo.r.squared
#>   <chr>    <int> <dbl> <int> <dbl> <dbl> <dbl>  <dbl>    <dbl>            <dbl>
#> 1 ssn_mod1    45     2     3  76.9  82.9  83.5  -38.4     43.0           0.585 
#> 2 ssn_mod2    45     2     3 123.  129.  129.   -61.4     43.4           0.0917