Compute robust clumpy scagnostic measure using MST

Source: R/robustscags.R

Compute robust clumpy scagnostic measure using MST

sc_clumpy_r(x, y)

# S3 method for default
sc_clumpy_r(x, y)

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

# S3 method for igraph
sc_clumpy_r(x, y)

Arguments

x

numeric vector of x values

y

numeric vector of y values

Value

A "numeric" object that gives the plot's robust 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_r(x,y))
#> Warning: There were 2123 warnings in `summarise()`.
#> The first warning was:
#> ℹ In argument: `clumpy = sc_clumpy_r(x, y)`.
#> ℹ In group 1: `feature = "barrier"`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> ℹ Run `dplyr::last_dplyr_warnings()` to see the 2122 remaining warnings.
#> # A tibble: 15 × 2
#>    feature    clumpy
#>    <chr>       <dbl>
#>  1 barrier     0.669
#>  2 clusters    0.582
#>  3 discrete    0.756
#>  4 disk        0.851
#>  5 gaps        0.544
#>  6 l-shape     0.524
#>  7 line        0.501
#>  8 nonlinear1  0.604
#>  9 nonlinear2  0.430
#> 10 outliers    0.573
#> 11 outliers2   0.545
#> 12 positive    0.524
#> 13 ring        0.747
#> 14 vlines      0.912
#> 15 weak        0.373
  sc_clumpy_r(datasaurus_dozen_wide$away_x, datasaurus_dozen_wide$away_y)
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to max; returning -Inf
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#> [1] 0.6708024