step_measure_moments() creates a specification of a recipe step that
calculates statistical moments from spectra.
Arguments
- recipe
A recipe object.
- moments
Character vector specifying which moments to calculate. Options:
"mean","sd","skewness","kurtosis","entropy". Default isc("mean", "sd", "skewness", "kurtosis").- weighted
Logical. If
TRUE, moments are weighted by location values. Default isFALSE.- measures
An optional character vector of measure column names.
- prefix
Prefix for output column names. Default is
"moment_".- role
Role for generated columns. Default is
"predictor".- trained
Logical indicating if the step has been trained.
- skip
Logical. Should the step be skipped when baking?
- id
Unique step identifier.
Details
This step calculates statistical moments that summarize the distribution of values in each spectrum:
| Moment | Description |
| mean | Mean value of the spectrum |
| sd | Standard deviation of values |
| skewness | Asymmetry of the distribution |
| kurtosis | "Tailedness" of the distribution |
| entropy | Shannon entropy (requires positive values) |
When weighted = TRUE, the location (x-axis) values are used as weights,
which can be useful for calculating center of mass or weighted statistics.
See also
Other measure-features:
step_measure_bin(),
step_measure_integrals(),
step_measure_ratios()
Examples
library(recipes)
rec <- recipe(water + fat + protein ~ ., data = meats_long) |>
update_role(id, new_role = "id") |>
step_measure_input_long(transmittance, location = vars(channel)) |>
step_measure_moments(moments = c("mean", "sd", "skewness")) |>
prep()
bake(rec, new_data = NULL)
#> # A tibble: 215 × 8
#> id water fat protein .measures moment_mean moment_sd moment_skewness
#> <int> <dbl> <dbl> <dbl> <meas> <dbl> <dbl> <dbl>
#> 1 1 60.5 22.5 16.7 [100 × 2] 2.97 0.270 0.222
#> 2 2 46 40.1 13.5 [100 × 2] 3.24 0.234 -0.311
#> 3 3 71 8.4 20.5 [100 × 2] 2.82 0.206 0.536
#> 4 4 72.8 5.9 20.7 [100 × 2] 3.09 0.238 0.540
#> 5 5 58.3 25.5 15.5 [100 × 2] 3.25 0.326 0.102
#> 6 6 44 42.7 13.7 [100 × 2] 3.48 0.262 -0.387
#> 7 7 44 42.7 13.7 [100 × 2] 3.44 0.249 -0.405
#> 8 8 69.3 10.6 19.3 [100 × 2] 2.87 0.280 0.338
#> 9 9 61.4 19.9 17.7 [100 × 2] 3.79 0.329 0.0588
#> 10 10 61.4 19.9 17.7 [100 × 2] 3.94 0.345 0.0582
#> # ℹ 205 more rows