single_variable_df_check

Function to check if a single variable data frame is valid

Provides methods for analyzing the dispersion of tabular datasets
with batched and ordered samples. Based on convex hull or integrated covariance
Mahalanobis, several indicators are implemented for inter and intra batch dispersion
analysis. It is designed to facilitate robust statistical assessment of data
variability, supporting applications in exploratory data analysis and quality
control, for such datasets as the one found in metabololomics studies.
For more details see Salanon (2024) <doi:10.1016/j.chemolab.2024.105148> and
Salanon (2025) <doi:10.1101/2025.08.01.668073>.

Etienne Jules

dispersionIndicators

Indicators for the Analysis of Dispersion of Datasets with
Batched and Ordered Samples

Brice Mulot

Elfried Salanon

INRAE (Institut national de recherche pour l'agriculture, l'alimentation et l'environnement) 

single_variable_df_check function

<dl><dt>df</dt>
<dd>Data frame containing 'batch', 'order', and 'value' columns.</dd>
<dt>name</dt>
<dd>Name of the data frame for error messages.</dd></dl>

Arguments

Function to check if a single variable data frame is valid — single_variable_df_check

<dl>

<dt>df</dt>
<dd>Data frame containing 'batch', 'order', and 'value' columns.</dd>


<dt>name</dt>
<dd>Name of the data frame for error messages.</dd>

</dl>

single_variable_df_check: Function to check if a single variable data frame is valid

Description

Usage

Value

Arguments