Package index • cssr

All functions

clusterRepLasso(): Select features via the cluster representative lasso (Bühlmann et. al. 2013)
css(): Cluster Stability Selection
cssLasso(): Provided fitfun implementing the lasso
cssPredict(): Wrapper function to generate predictions from cluster stability selected model in one step
cssSelect(): Obtain a selected set of clusters and features using cluster stability selection
genClusteredData(): Generate randomly sampled data including noisy observations of latent variables
genClusteredDataWeighted(): Generate randomly sampled data including noisy observations of latent variables, where proxies differ in their relevance (noise level)
genClusteredDataWeightedRandom(): Generate randomly sampled data including noisy observations of latent variables, where proxies differ in their relevance (noise level)
getCssDesign(): Obtain a design matrix of cluster representatives
getCssPreds(): Fit model and generate predictions from new data
getCssSelections(): Obtain a selected set of clusters and features
getLassoLambda(): Get lambda value for lasso
getModelSize(): Automated estimation of model size
getNoiseVar(): Get variance of noise to add to Z in order to yield proxies X with desired correlations with Z
print(<cssr>): Print cluster stability selection output
printCssDf(): Prepares a data.frame summarazing cluster stability selection output to print
protolasso(): Select features via the protolasso (Reid and Tibshirani 2016)
selected(): Extract the selected clusters or features from cluster stability selection
print(<summary.cssr>) summary(<cssr>): Summarize cluster stability selection output