Python notebook on GtSt testing procedures on the LARS path. Code associated with the manuscript "Multiple Testing and Variable Selection along Least Angle Regression's path" (J.-M. Azaïs & Y. De Castro)
In this work, we consider learning sparse models in large scale setting, where the number of samples and the feature dimension can grow as large as millions or billions. Two immediate issues occur under such challenging scenarios: (i) com- putational cost; (ii) memory overhead.
U statistici , regresija najmanjeg ugla (LARS) algoritam je za prilagođavanje modela linearne regresije visokodimenzionalnim podacima, koji je razvio Bradley Efron , Trevor Hastie , Iain Johnstone i Robert Tibshirani .