Compute clumpy scagnostic measure using MST

Compute clumpy scagnostic measure using MST

sc_clumpy(x, y)

# S3 method for default
sc_clumpy(x, y)

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

# S3 method for igraph
sc_clumpy(x, y)

Arguments

x

numeric vector of x values

y

numeric vector of y values

Value

A "numeric" object that gives the plot's clumpy 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(clumpy = sc_clumpy(x,y))
#> # A tibble: 15 × 2
#>    feature    clumpy
#>    <chr>       <dbl>
#>  1 barrier     0.810
#>  2 clusters    0.802
#>  3 discrete    0.949
#>  4 disk        0.913
#>  5 gaps        0.908
#>  6 l-shape     0.869
#>  7 line        0.870
#>  8 nonlinear1  0.988
#>  9 nonlinear2  0.742
#> 10 outliers    0.866
#> 11 outliers2   0.960
#> 12 positive    0.798
#> 13 ring        0.929
#> 14 vlines      0.907
#> 15 weak        0.760
  sc_clumpy(datasaurus_dozen_wide$away_x, datasaurus_dozen_wide$away_y)
#> [1] 0.8834582