gLVInterNetworks-package: Inference of interaction networks based on generalised Lotka...

Description Details Author(s) References Examples

Description

Inference of interaction networks based on the parameterization of generalized Lotka Volterra models on timeseries data

Details

The DESCRIPTION file: This package was not yet installed at build time.

Index: This package was not yet installed at build time.
~~ An overview of how to use the package, including the most important functions ~~

Author(s)

Lukas Hirsch, Florian Centler Maintainer: Lukas Hirsch <lukashirsch@gmail.com>

References

~~ Literature or other references for background information ~~

Examples

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library(gLVInterNetworks)
data <- gLVgenerateData(species = 2, number_of_interactions = 2, timepoints = 100, noise = 0.01, testData = 20)
## Not run: plot(data, type = "l")
lr <- gLVlinearRegression(data, regularization = TRUE, alpha = 0)
## Not run: summary(lr)
## Not run: plot(lr, type = "l")
## Not run: points(data)
nlr <- gLVnonlinearRegression(data, parms0 = lr$Parms)
## Not run: summary(nlr)
## Not run: plot(nlr, type = "l")
## Not run: points(data)
## Not run: par(mfrow = c(1,2))
## Not run: plotGraph(data, vsize = 0.2, main = "Original interaction network", verbose = TRUE )
## Not run: plotGraph(nlr, vsize = 0.2, main = "Inferred interaction network", verbose = TRUE)
ident <- sensitivityAnalysis(nlr$Parms) 
## Print summary of sensitivity matrix
summary(ident$sens)
## Print collinearity index for all parameters together
ident$coll[ident$coll[,"N"]==length(data$Parms),]

lkshrsch/gLVInterNetworks documentation built on May 21, 2019, 7:33 a.m.