Non-Crossing Additive Regression Quantiles and Non-Parametric
Growth Charts
Description
Fits non-crossing regression quantiles as a function of linear covariates and multiple smooth terms, including varying coefficients, via B-splines with L1-norm difference penalties.
Random intercepts and variable selection are allowed via the lasso penalties.
The smoothing parameters are estimated as part of the model fitting, see Muggeo and others (2021) . Monotonicity and concavity
constraints on the fitted curves are allowed, see Muggeo and others (2013) ,
and also or some code examples.