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Glance at many fitted model objects

Source: R/glances.R, R/glances_glm.R
glances.Rd

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

Usage

glances(object, ..., sort_by = "AICc", decreasing = FALSE)

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

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

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

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

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

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

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

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

Arguments

object

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

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

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 × 10
#>   model     n     p  npar value   AIC  AICc logLik deviance pseudo.r.squared
#>   <chr> <int> <dbl> <int> <dbl> <dbl> <dbl>  <dbl>    <dbl>            <dbl>
#> 1 lmod     30     4     1 -1.68 0.323 0.466  0.838     26.0            0.277
#> 2 spmod    30     4     3 -5.85 0.150 1.07   2.92      26.0            0.396
glances(lmod, spmod, sort_by = "logLik", decreasing = TRUE)
#> # 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 spmod    30     4     3 -5.85 0.150 1.07   2.92      26.0            0.396
#> 2 lmod     30     4     1 -1.68 0.323 0.466  0.838     26.0            0.277