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Big data statistical analysis for high-dimensional models is made possible by modifying lasso.proj()...
Unified interface for the estimation of causal networks, including the methods 'backShift' (from pac...
Implementation of multiple approaches to perform inference in high-dimensional models.
When testing multiple hypotheses simultaneously, this package provides functionality to calculate a ...
Confidence intervals for causal effects, using data collected in different experimental or environme...
Node harvest is a simple interpretable tree-like estimator for high-dimensional regression and class...
Low-dimensional embedding, using Random Forests for multiclass classification
Quantile Regression Forests is a tree-based ensemble method for estimation of conditional quantiles....
Relaxed Lasso is a generalisation of the Lasso shrinkage
technique for linear regression. Bot...
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