Bounded_weights

Add weights to the data, bound at a maximum.

Determine the chlorophyll a (Chl a) concentrations of different
phytoplankton groups based on their pigment biomarkers. The method uses
non-negative matrix factorisation and simulated annealing to minimise error
between the observed and estimated values of pigment concentrations
(Hayward et al. (2023) <doi:10.1002/lom3.10541>).
The approach is similar to the widely used 'CHEMTAX' program
(Mackey et al. 1996) <doi:10.3354/meps144265>, but is more straightforward,
accurate, and not reliant on initial guesses for the pigment to Chl a
ratios for phytoplankton groups.

Alexander Hayward

phytoclass

Estimate Chla Concentrations of Phytoplankton Groups

Tylar Murray

Sebastian Di Geronimo

Mohd Aasim Maqsood Khan

Andy McKenzie

Bounded_weights function

<dl><dt>S</dt>
<dd>Sample data matrix – a matrix of pigment samples</dd>
<dt>weight.upper.bound</dt>
<dd>Upper bound for weights (default is 30)</dd></dl>

Arguments

Add weights to the data, bound at a maximum. — Bounded_weights

<dl>

<dt>S</dt>
<dd>Sample data matrix – a matrix of pigment samples</dd>


<dt>weight.upper.bound</dt>
<dd>Upper bound for weights (default is 30)</dd>

</dl>

Bounded_weights: Add weights to the data, bound at a maximum.

Description

Usage

Value

Arguments

Examples