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Horns index for each CLOSURE sample

Source: R/horns-analyze.R
closure_horns_analyze.Rd

Following up on closure_generate(), you can call closure_horns_analyze() to compute the horns index for each individual sample and compute summary statistics on the distribution of these indices. See horns() for the metric itself.

This adds more detail to the "horns" and "horns_uniform" columns in the output of closure_generate(), where "horns" is the overall mean of the per-sample indices found here.

closure_horns_histogram() draws a quick barplot to reveal the distribution of horns values. The scale is fixed between 0 and 1.

Usage

closure_horns_analyze(data)

closure_horns_histogram(
  data,
  bar_alpha = 0.8,
  bar_color = "#5D3FD3",
  bar_binwidth = 0.0025,
  text_size = 12
)

Arguments

data

For closure_horns_analyze(), a list returned by closure_generate(). For closure_horns_histogram(), a list returned by closure_horns_analyze().

bar_alpha

Numeric (length 1). Opacity of the bars. Default is 0.8.

bar_color

String (length 1). Color of the bars. Default is "#5D3FD3", a purple color.

bar_binwidth

Width of the bins that divide up the x-axis, passed on to ggplot2::geom_histogram(). Default is 0.0025.

text_size

Numeric. Base font size in pt. Default is 12.

Value

closure_horns_analyze() returns a named list of two tibbles (data frames):

  • horns_metrics: Summary statistics of the distribution of horns index values:

    • mean, uniform: same as horns and horns_uniform from closure_generate()'s output.

    • sd: double. Standard deviation.

    • cv: double. Coefficient of variation, i.e., sd / mean.

    • mad: double. Median absolute deviation; see stats::mad().

    • min, median, max: double. Minimum, median, and maximum horns index.

    • range: double. Equal to max - min.

  • horns_results:

    • id: integer. Uniquely identifies each horns index, just like their corresponding samples in closure_generate().

    • horns: double. Horns index for each individual sample.

closure_horns_histogram() returns a ggplot object.

Details

The "mad" column overrides a default of stats::mad(): adjusting the result via multiplication by a constant (about 1.48). This assumes a normal distribution, which generally does not seem to be the case with horns index values. Here, the constant is set to 1.

Examples

data <- closure_generate(
  mean = "2.9",
  sd = "0.5",
  n = 70,
  scale_min = 1,
  scale_max = 5
)

data_horns <- closure_horns_analyze(data)
data_horns
#> $closure_generate_inputs
#> # A tibble: 1 × 7
#>   mean  sd        n scale_min scale_max rounding   threshold
#>   <chr> <chr> <dbl>     <dbl>     <dbl> <chr>          <dbl>
#> 1 2.9   0.5      70         1         5 up_or_down         5
#> 
#> $horns_metrics
#> # A tibble: 1 × 9
#>     mean uniform      sd    cv     mad    min median    max  range
#>    <dbl>   <dbl>   <dbl> <dbl>   <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
#> 1 0.0643     0.5 0.00690 0.107 0.00551 0.0511 0.0654 0.0737 0.0227
#> 
#> $horns_results
#> # A tibble: 219 × 2
#>       id  horns
#>    <int>  <dbl>
#>  1     1 0.0563
#>  2     2 0.0523
#>  3     3 0.0563
#>  4     4 0.0635
#>  5     5 0.0523
#>  6     6 0.0706
#>  7     7 0.0594
#>  8     8 0.0553
#>  9     9 0.0635
#> 10    10 0.0706
#> # ℹ 209 more rows
#> 

closure_horns_histogram(data_horns)