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