datatrue_coda

A data set of 200 simulated 'true' data, from which the observations are deduced, with three observed variables and two groups, compositional

datasets

The qda() function from package 'MASS' is extended to calculate a weighted linear (LDA) and quadratic discriminant analysis (QDA) by changing the group variances and group means based on cell-wise uncertainties.
The uncertainties can be derived e.g. through relative errors for each individual measurement (cell), not only row-wise or column-wise uncertainties.
The method can be applied compositional data (e.g. portions of substances, concentrations) and non-compositional data.

Solveig Pospiech

vdar

Discriminant Analysis Incorporating Individual Uncertainties

datatrue_coda function

A data frame with 200 rows and 4 columns<dl class="dl-horizontal">
 <dt>Var1</dt><dd>simulated variable, compositional</dd>
 <dt>Var2</dt><dd>simulated variable, compositional</dd>
 <dt>Var3</dt><dd>simulated variable, compositional</dd>
 <dt>Group</dt><dd>Factor with levels 'Group 1' and 'Group 2'</dd>
</dl>

Format

Simulated true compositional data — datatrue_coda

A data frame with 200 rows and 4 columns<dl class='dl-horizontal'>
 <dt>Var1</dt><dd>simulated variable, compositional</dd>
 <dt>Var2</dt><dd>simulated variable, compositional</dd>
 <dt>Var3</dt><dd>simulated variable, compositional</dd>
 <dt>Group</dt><dd>Factor with levels 'Group 1' and 'Group 2'</dd>
</dl>

datatrue_coda: Simulated true compositional data

Description

Usage

Arguments

Format