R: Linear Programming Model for Network Inference

# Linear Programming Model for Network Inference

## Documentation for package ‘lpNet’ version 2.44.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

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