amean_bymot_jack

a numeric vector. The vector <code>fobs</code> contains the
quantitative performances of assemblages.

fobs

an integer vector of length <code>2</code>.
The vector specifies the parameters for jackknife method.
The first integer <code>jack[1]</code> specifies the size of subset,
the second integer <code>jack[2]</code> specifies the number of subsets.

jack

Take a vector <code>fobs</code>
of performances of assemblages
that share the same assembly motif,
and return a vector of performances predicted
as the arithmetic mean
of performances of other assemblages.

internal

Cluster together the components that make up an interactive
system on the basis of their functional redundancy
for one or more collective, systemic performances.
Plot the hierarchical tree of component clusters,
the modelled and predicted performances of component assemblages,
and other results associated with a functional clustering.
Test and prioritize the significance of the different components
that make up the interactive system,
of the different assemblages of components that make up the dataset,
and of the different performances observed on the component assemblages.
The method finds application in ecology, for instance,
where the system is an ecosystem, the components are organisms or species,
and the systemic performance is the production of biomass
or the respiration of the ecosystem.
The method is extensively described in
Jaillard B, Deleporte P, Loreau M, Violle C (2018)
"A combinatorial analysis using observational data identifies species
that govern ecosystem functioning"
<doi:10.1371/journal.pone.0201135>.

Beno<c3><ae>t Jaillard

amean_bymot_jack: Arithmetic mean of performances by assembly motif using jackknife method

Description

Usage

Arguments

Value

Details

See Also