Select Intervals Suited for Functional Regression

Interval fusion and selection procedures for regression with functional inputs. Methods include a semiparametric approach based on Sliced Inverse Regression (SIR), as described in (standard ridge and sparse SIR are also included in the package) and a random forest based approach, as described in .

SISIR

SISIR is an R package designed to handle function data (e.g., curved sampled on a discrete time grid). Implemented methods can perform interval fusion and selection procedures in regression models with functional inputs. They include a semiparametric approach based on Sliced Inverse Regression (SIR), as described in doi:10.1007/s11222-018-9806-6 (standard ridge and sparse SIR are also included in the package) and a random forest based approach, as described in doi:10.1002/sam.11705.