Compute skinny scagnostic measure

Compute skinny scagnostic measure

sc_skinny(x, y)

# S3 method for default
sc_skinny(x, y)

# S3 method for scree
sc_skinny(x, y = NULL)

# S3 method for list
sc_skinny(x, y = NULL)

Arguments

x

numeric vector of x values

y

numeric vector of y values

Value

A "numeric" object that gives the plot's skinny score.

Examples

  require(ggplot2)
  require(dplyr)
  ggplot(features, aes(x=x, y=y)) +
     geom_point() +
     facet_wrap(~feature, ncol = 5, scales = "free")

  features %>% group_by(feature) %>% summarise(skinny = sc_skinny(x,y))
#> # A tibble: 15 × 2
#>    feature    skinny
#>    <chr>       <dbl>
#>  1 barrier    0.242 
#>  2 clusters   0.536 
#>  3 discrete   0.0711
#>  4 disk       0.104 
#>  5 gaps       0.219 
#>  6 l-shape    0.727 
#>  7 line       0.861 
#>  8 nonlinear1 0.307 
#>  9 nonlinear2 0.672 
#> 10 outliers   0.466 
#> 11 outliers2  0.246 
#> 12 positive   0.393 
#> 13 ring       0.709 
#> 14 vlines     0.127 
#> 15 weak       0.148 
  sc_skinny(datasaurus_dozen_wide$away_x, datasaurus_dozen_wide$away_y)
#> [1] 0.2764928