qdODEmod

quasi-dynamic lotka volterra model

Most existing approaches for network reconstruction can only infer an overall network
and, also, fail to capture a complete set of network properties. To address these issues,
a new model has been developed, which converts static data into their 'dynamic' form.
'idopNetwork' is an 'R' interface to this model, it can inferring informative, dynamic,
omnidirectional and personalized networks. For more information on functional
clustering part, see Kim et al. (2008) <doi:10.1534/genetics.108.093690>,
Wang et al. (2011) <doi:10.1093/bib/bbr032>. For more information on our model,
see Chen et al. (2019) <doi:10.1038/s41540-019-0116-1>, and Cao et al. (2022)
<doi:10.1080/19490976.2022.2106103>.

Ang Dong

idopNetwork

A Network Tool to Dissect Spatial Community Ecology

qdODEmod function

<dl><dt>Time</dt>
<dd>vector of time point</dd>
<dt>State</dt>
<dd>vector of ODE initial state</dd>
<dt>Pars</dt>
<dd>vector for unknown ODE parameters</dd>
<dt>power_par</dt>
<dd>matrix of power equation parameters for dependent effect</dd></dl>

Arguments

quasi-dynamic lotka volterra model — qdODEmod

<dl>

<dt>Time</dt>
<dd>vector of time point</dd>


<dt>State</dt>
<dd>vector of ODE initial state</dd>


<dt>Pars</dt>
<dd>vector for unknown ODE parameters</dd>


<dt>power_par</dt>
<dd>matrix of power equation parameters for dependent effect</dd>

</dl>

qdODEmod: quasi-dynamic lotka volterra model

Description

Usage

Value

Arguments