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quantregGrowth (version 1.7-1)

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.

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Version

Install

install.packages('quantregGrowth')

Monthly Downloads

450

Version

1.7-1

License

GPL

Maintainer

Vito MR Muggeo

Last Published

May 20th, 2024

Functions in quantregGrowth (1.7-1)

SiChildren

Age, height and weight in a sample of Italian children
charts

Easy computing growth charts
print.gcrq

Print method for the gcrq class
logLik.gcrq

Log Likelihood, AIC and BIC for gcrq objects
growthData

Simulated data to illustrate capabilities of the package
ps

Specifying a smooth term in the gcrq formula.
predict.gcrq

Prediction for "gcrq" objects
gcrq

Growth charts regression quantiles with automatic smoothness estimation
vcov.gcrq

Variance-Covariance Matrix for a Fitted 'gcrq' Model
ncross.rq.fitXB

Estimation of noncrossing regression quantiles with monotonicity restrictions.
summary.gcrq

Summarizing model fits for growth charts regression quantiles
plot.gcrq

Plot method for gcrq objects
quantregGrowth-package

Non-Crossing Additive Regression Quantiles and Non-Parametric Growth Charts.