R: A Network Tool to Dissect Spatial Community Ecology

# A Network Tool to Dissect Spatial Community Ecology

## Documentation for package ‘idopNetwork’ version 0.1.2

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

bifun_clu | main function for bifunctional clustering
bifun_clu_convert | convert result of bifunctional clustering result
bifun_clu_parallel | parallel version for functional clustering
bifun_clu_plot | bifunctional clustering plot
biget_par_int | acquire initial parameters for functional clustering
bipower_equation_plot | plot power equation fitting results for bi-variate model
biqdODE_plot_all | plot all decompose plot for two data
biqdODE_plot_base | plot single decompose plot for two data
biQ_function | Q-function to replace log-likelihood function
darken | make color more dark
data_cleaning | remove observation with too many 0 values
data_match | match power_equation fit result for bi-variate model
fun_clu | main function for functional clustering
fun_clu_BIC | plot BIC results for functional clustering
fun_clu_convert | convert result of functional clustering result
fun_clu_parallel | parallel version for functional clustering
fun_clu_plot | functional clustering plot
fun_clu_select | select result of functional clustering result
get_biSAD1 | generate biSAD1 covariance matrix
get_interaction | Lasso-based variable selection
get_legendre_matrix | generate legendre matrix
get_legendre_par | use legendre polynomials to fit a given data
get_mu | curve fit with modified logistic function
get_mu2 | generate mean vectors with ck and stress condition
get_par_int | acquire initial parameters for functional clustering
get_SAD1_covmatrix | generate standard SAD1 covariance matrix
gut_microbe | gut microbe OTU data (species level)
legendre_fit | generate curve based on legendre polynomials
logsumexp | calculate log-sum-exp values
mustard_microbe | mustard microbe OTU data
network_conversion | convert ODE results(ODE_solving2) to basic network plot table
network_maxeffect | convert ODE results(ODE_solving2) to basic network plot table
network_plot | generate network plot
normalization | min-max normalization
power_equation | use power equation parameters to generate y values
power_equation_all | use power equation to fit observed values
power_equation_base | use power equation to fit observed values
power_equation_fit | use power equation to fit given dataset
power_equation_plot | plot power equation fitting results
qdODEmod | quasi-dynamic lotka volterra model
qdODEplot_convert | convert qdODE results to plot data
qdODE_all | wrapper for qdODE model
qdODE_fit | legendre polynomials fit to qdODE model
qdODE_ls | least-square fit for qdODE model
qdODE_parallel | wrapper for qdODE_all in parallel version
qdODE_plot_all | plot all decompose plot
qdODE_plot_base | plot single decompose plot
Q_function | Q-function to replace log-likelihood function