R package ppls: Penalized Partial Least Squares. This package contains linear and nonlinear regression methods based on Partial Least Squares and Penalization Techniques. Model parameters are selected via cross-validation, and confidence intervals ans tests for the regression coefficients can be conducted via jackknifing.
Keywords for this software
References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
- Roy, Vivekananda; Tan, Aixin; Flegal, James M.: Estimating standard errors for importance sampling estimators with multiple Markov chains (2018)
- Ghosh, Joyee; Tan, Aixin: Sandwich algorithms for Bayesian variable selection (2015)
- Martin Bilodeau; Pierre Micheaux; Smail Mahdi: The R Package groc for Generalized Regression on Orthogonal Components (2015) not zbMATH
- Goldsmith, Jeff; Scheipl, Fabian: Estimator selection and combination in scalar-on-function regression (2014)
- Magidson, Jay: Correlated component regression: re-thinking regression in the presence of near collinearity (2013)