Description Usage Arguments Value References Examples
View source: R/HMFmethod_mainFunction.R
This function performs system identification to infer the connectivity and dynamics of a linear network model (Anderson et al., 2017).
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datHMF |
The data matrix with scaled measurements measurements. Scaled center measurements are provided for each measurement/annotation (e.g., gene/organ) combination. This format is produced by scale_zeroOne(). Defaults to datHMF. |
N_mRanges |
The number of m-value sets to evaluate. |
alpha |
The L1 regularization terms for constraining the regression. Defaults to seq(0,1,0.2). |
nlambda |
The number of L2 regularization terms for consideration. Defaults to 10. |
Mall |
A set of m-values. Defaults to NULL. |
Msc |
A scale factor that determines the M value (M = max(m)) corresponding to the largest range of m-values. Mmax <- ceiling(Msc * Np / 2) where Np = number of parameters. |
n |
Highest order of the system (n=1 for the first degree system that this analysis was designed for). |
dt |
Simulation time step |
epsilon |
Term for computing simulation error. Defaults to 10^(-10). |
Harg0 |
If omega_0 is equal to zero (x=0), set omega_0 to Harg0 (w=Harg0). |
Error data for all simulations, simulation data for the best simulation, a parameter matrix for the best simulation.
http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005627
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