Cook's outlier detection on gradient positions vs densities

Assuming a linear relationship between the gradient_position and gradient_pos_density, this function will plot any potential outliers using Cook's distance and a defined sensitivity. The lower the sensitivity, the more likely outliers will be flagged.

Usage

plot_density_outliers(sample_data, sensitivity = 4)

Arguments

sample_data

(qsip_sample_data or qsip_data) A qsip object with sample data

sensitivity

(numeric, default: 4) A sensitivity value, with lower values being more sensitive to outlier detection

Value

A ggplot object

See also

Other "visualizations": plot_feature_curves(), plot_filter_results(), plot_sample_curves(), plot_source_wads()