Those are support for the functions fp() and pp.
It is not intended to be called directly by users.
gamlss.fp(x, y, w, npoly = 2, xeval = NULL)
gamlss.pp(x, y, w)the x for function gamlss.fp is referred to the design matric of the specific parameter model (not to be used by the user)
the y for function gamlss.fp is referred to the working variable of the specific parameter model (not to be used by the user)
the w for function gamlss.fp is referred to the iterative weight variable of the specific parameter model (not to be used by the user)
a positive indicating how many fractional polynomials should be considered in the fit. Can take the values 1, 2 or 3 with 2 as default
used in prediction
Returns a list with
fitted
residuals
the trace of the smoothing matrix
the value of the smoothing parameter
the coefficients from the smoothing fit
the variance of the coefficients
Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.
Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, http://www.jstatsoft.org/v23/i07.
Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.
(see also http://www.gamlss.org/).