bifun_clu_convert

convert result of bifunctional clustering result

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

bifun_clu_convert function

<dl><dt>result</dt>
<dd>list directly from bifun_clu_parallel function</dd>
<dt>best.k</dt>
<dd>scale of BIC-determined cluster number</dd></dl>

Arguments

convert result of bifunctional clustering result — bifun_clu_convert

<dl>

<dt>result</dt>
<dd>list directly from bifun_clu_parallel function</dd>


<dt>best.k</dt>
<dd>scale of BIC-determined cluster number</dd>

</dl>

bifun_clu_convert: convert result of bifunctional clustering result

Description

Usage

Value

Arguments