It seems that there are two methods and packages in R to calculate the Percentile curves based on LMS (Lambda for the skew, Mu for the median, and Sigma for the generalized coefficient of variation; Cole, 1990).
-- GAMLSS (Generalized Additive Model for Location, Scale and Shape)
-- VGAM (Vector generalized additive model)
Which one of these two techniques and their corresponding R packages can estimate more accurate estimation for percentile curves?
Among lms.bcn (LMS Quantile Regression with a Box-Cox Transformation to Normality) and lms.yjn (LMS quantile regression with the Yeo-Johnson transformation to normality) in VGAM method/package, which function is more appropriate to calculate the percentile curves?
Thank you so much for your time and advice.