Correct sample density values using gradient position information

Used in conjunction with plot_density_outliers(), this function will correct the gradient_pos_density values for outliers based on the gradient_position values. A linear model is built using the gradient_position and gradient_pos_density, and if the Cook's outlier value is above the cutoff, then that sample's gradient_pos_density value is replaced with the fitted value. If it isn't above the cut-off, then no correction is made for that sample.

Usage

correct_gradient_pos_density(sample_data, sensitivity = 4)

Arguments

sample_data

(qsip_sample_data) A qsip object with sample data

sensitivity

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

Value

A qsip_sample_data object with corrected gradient_pos_density values