parameter_sensitivity_analysis: Parameter Sensitivity Analysis

In topolow: Force-Directed Euclidean Embedding of Dissimilarity Data

Parameter Sensitivity Analysis

Description

Analyzes the sensitivity of the model performance (measured by MAE) to changes in a single parameter. This function bins the parameter range to identify the minimum MAE for each bin, helping to understand how robust the model is to parameter choices.

Usage

parameter_sensitivity_analysis(
  param,
  samples,
  bins = 30,
  mae_col = "Holdout_MAE",
  threshold_pct = 5,
  min_samples = 1
)

Arguments

param	The character name of the parameter to analyze.
samples	A data frame containing parameter samples and performance metrics.
bins	The integer number of bins to divide the parameter range into.
mae_col	The character name of the column containing the Mean Absolute Error (MAE) values.
threshold_pct	A numeric percentage above the minimum MAE to define an acceptable performance threshold.
min_samples	The integer minimum number of samples required in a bin for it to be included in the analysis.

Details

The function performs these steps:

1. Cleans the input data using Median Absolute Deviation (MAD) to remove outliers.

2. Bins the parameter values into equal-width bins.

3. Calculates the minimum MAE within each bin to create an empirical performance curve.

4. Identifies a performance threshold based on a percentage above the global minimum MAE.

5. Returns an S3 object for plotting and further analysis.

Value

An object of class "parameter_sensitivity" containing:

param_values	Vector of parameter bin midpoints
min_mae	Vector of minimum MAE values per bin
param_name	Name of analyzed parameter
threshold	Threshold value (default: min. +5%)
min_value	Minimum MAE value across all bins
sample_counts	Number of samples per bin

topolow documentation built on Aug. 31, 2025, 1:07 a.m.