Title: Growth Charts via Regression Quantiles
Description: Fits non-crossing regression quantiles as a function of linear covariates and a smooth terms via B-splines with difference penalties.

Description: Fits non-crossing regression quantiles as a function of linear covariates and multiple smooth terms via B-splines with L1-norm difference penalties. See Muggeo, Sciandra, Tomasello and Calvo (2013) <doi:10.1007/s10651-012-0232-1> and <doi:10.13140/RG.2.2.12924.85122> per same example code.

Description: Fits non-crossing regression quantiles as a function of linear covariates and multiple smooth terms via B-splines with L1-norm difference penalties. See Muggeo, Sciandra, Tomasello and Calvo (2013) <doi:10.1007/s10651-012-0232-1> and <doi:10.13140/RG.2.2.12924.85122> for some code example.

c("aut", "cre"), email = "vito.muggeo@unipa.it", comment=c(ORCID="0000-0002-3386-4054")))
Description: Fits non-crossing regression quantiles as a function of linear covariates and multiple smooth terms via B-splines with L1-norm difference penalties. Monotonicity constraints on the fitted curves are allowed. See Muggeo, Sciandra, Tomasello and Calvo (2013) <doi:10.1007/s10651-012-0232-1> and <doi:10.13140/RG.2.2.12924.85122> for some code example.

Title: Growth Charts via Smooth Regression Quantiles with Automatic
Smoothness Estimation and Additive Terms
Description: Fits non-crossing regression quantiles as a function of linear covariates and multiple smooth terms via B-splines with L1-norm difference penalties. The smoothing parameters are estimated as part of the model fitting. Monotonicity and concavity constraints on the fitted curves are allowed. See Muggeo, Sciandra, Tomasello and Calvo (2013) <doi:10.1007/s10651-012-0232-1> and <doi:10.13140/RG.2.2.12924.85122> for some code examples.
Smoothing parameter selection with additive terms is discussed in Muggeo and others (2020) <doi:10.1177/1471082X20929802>.

Depends: R (>= 3.5.0), quantreg, splines

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.
The smoothing parameters are estimated as part of the model fitting, see Muggeo and others (2021) <doi:10.1177/1471082X20929802>. Monotonicity and concavity
constraints on the fitted curves are allowed, see Muggeo and others (2013) <doi:10.1007/s10651-012-0232-1> and also <doi:10.13140/RG.2.2.12924.85122> for some code examples.