Linear Programming Model for Network Inference


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Documentation for package ‘lpNet’ version 2.38.0

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lpNet-package Network Inference Of Perturbation Data Using a Linear Programming Approach.
calcActivation Calculate Activation Matrix
calcPredictionKfoldCV Calculate Predicted Observation.
calcPredictionLOOCV Calculate Predicted Observation.
calcRangeLambda Compute Range Of Penalty Parameter Lambda.
doILP Do The Network Inference With The Linear Programming Approach.
generateTimeSeriesNetStates Generate Time Series Network States
getAdja Get Adjacency Matrix.
getBaseline Get Baseline Vector.
getEdgeAnnot Get the annotation of the edges.
getObsMat Get Observation Matrix.
getSampleAdja Get The Sample Adjacency.
getSampleAdjaMAD Get The Sample Adjacency.
kfoldCV Cross-validation
loocv Cross-validation
lpNet Network Inference Of Perturbation Data Using a Linear Programming Approach.
summarizeRepl Summarize Replicate Measurements