A Network Tool to Dissect Spatial Community Ecology

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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