Robust Regression with Compositional Covariates

Documentation for package ‘robregcc’ version 1.0

classo	Estimate parameters of linear regression model with compositional covariates using method suggested by Pixu shi.
coef_cc	Extract coefficients estimate from the sparse version of the robregcc fitted object.
cpsc_nsp	Principal sensitivity component analysis with compositional covariates in non-sparse setting.
cpsc_sp	Principal sensitivity component analysis with compositional covariates in sparse setting.
plot_cv	Plot cross-validation error plot
plot_path	Plot solution path at different value of lambda
plot_resid	Plot residuals estimate from robregcc object
residuals	Extract residuals estimate from the sparse version of the robregcc fitted object.
residuals.robregcc	Extract residuals estimate from the sparse version of the robregcc fitted object.
robregcc_nsp	Robust model estimation approach for regression with compositional covariates.
robregcc_option	Control parameter for model estimation:
robregcc_sim	Simulation data
robregcc_sp	Robust model estimation approach for regression with compositional covariates.
simulate_robregcc_nsp	Simulated date for testing functions in the robregcc package (non-sparse setting).
simulate_robregcc_sp	Simulated date for testing functions in the robregcc package (sparse setting).