idopNetwork0.1.2 package

main function for bifunctional clustering

convert result of bifunctional clustering result

parallel version for functional clustering

bifunctional clustering plot

acquire initial parameters for functional clustering

plot power equation fitting results for bi-variate model

Q-function to replace log-likelihood function

plot all decompose plot for two data

plot single decompose plot for two data

make color more dark

remove observation with too many 0 values

match power_equation fit result for bi-variate model

main function for functional clustering

plot BIC results for functional clustering

convert result of functional clustering result

parallel version for functional clustering

functional clustering plot

select result of functional clustering result

generate biSAD1 covariance matrix

Lasso-based variable selection

generate legendre matrix

use legendre polynomials to fit a given data

curve fit with modified logistic function

generate mean vectors with ck and stress condition

acquire initial parameters for functional clustering

generate standard SAD1 covariance matrix

generate curve based on legendre polynomials

calculate log-sum-exp values

convert ODE results(ODE_solving2) to basic network plot table

convert ODE results(ODE_solving2) to basic network plot table

generate network plot

min-max normalization

use power equation parameters to generate y values

use power equation to fit observed values

use power equation to fit observed values

use power equation to fit given dataset

plot power equation fitting results

Q-function to replace log-likelihood function

wrapper for qdODE model

legendre polynomials fit to qdODE model

least-square fit for qdODE model

wrapper for qdODE_all in parallel version

plot all decompose plot

plot single decompose plot

quasi-dynamic lotka volterra model

convert qdODE results to plot data