glances() repeatedly calls glance() on several
fitted model objects and binds the output together, sorted by a column of interest.
glances(object, ...)
# S3 method for splm
glances(object, ..., sort_by = "AICc", decreasing = FALSE, warning = TRUE)
# S3 method for spautor
glances(object, ..., sort_by = "AICc", decreasing = FALSE, warning = TRUE)
# S3 method for splm_list
glances(object, ..., sort_by = "AICc", decreasing = FALSE, warning = TRUE)
# S3 method for spautor_list
glances(object, ..., sort_by = "AICc", decreasing = FALSE, warning = TRUE)
# S3 method for spglm
glances(object, ..., sort_by = "AICc", decreasing = FALSE, warning = TRUE)
# S3 method for spgautor
glances(object, ..., sort_by = "AICc", decreasing = FALSE, warning = TRUE)
# S3 method for spglm_list
glances(object, ..., sort_by = "AICc", decreasing = FALSE, warning = TRUE)
# S3 method for spgautor_list
glances(object, ..., sort_by = "AICc", decreasing = FALSE, warning = TRUE)A fitted model object from splm(), spautor(), spglm(), or spgautor().
Additional fitted model objects. Ignored
if object has class splm_list, spautor_list, spglm_list, or spgautor_list.
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".
Whether sort_by should sort by decreasing order? The default is FALSE.
Whether a warning is displayed when model comparisons violate certain rules.
The default is TRUE.
A tibble where each row represents the output of glance() for
each fitted model object.
lmod <- splm(z ~ water + tarp,
data = caribou,
spcov_type = "none"
)
spmod <- splm(z ~ water + tarp,
data = caribou,
spcov_type = "exponential", xcoord = x, ycoord = y
)
glances(lmod, spmod)
#> # A tibble: 2 × 11
#> model n p npar value AIC AICc BIC logLik deviance
#> <chr> <int> <dbl> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 lmod 30 4 1 -1.68 0.323 0.466 1.72 0.838 26
#> 2 spmod 30 4 3 -5.85 0.150 1.07 4.35 2.92 26
#> # ℹ 1 more variable: pseudo.r.squared <dbl>
glances(lmod, spmod, sort_by = "logLik", decreasing = TRUE)
#> # A tibble: 2 × 11
#> model n p npar value AIC AICc BIC logLik deviance
#> <chr> <int> <dbl> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 spmod 30 4 3 -5.85 0.150 1.07 4.35 2.92 26
#> 2 lmod 30 4 1 -1.68 0.323 0.466 1.72 0.838 26
#> # ℹ 1 more variable: pseudo.r.squared <dbl>