Generalised (Pseudo) R-squared for GAMLSS models
This function gives the generalised R-squared of Nagelkerke (1991) for a GAMLSS model.
Rsq(object, type = c("Cox Snell","Cragg Uhler","both"))object |
a GAMLSS object |
type |
which definition of R squared. Can be the "Cox Snell" or the Nagelkerke, "Cragg Uhler" or "both". |
The Rsq() function uses the definition for R-squared:
R-squared =1-(L(0)/L(fitted))^(2/n)
where L(0) is the null model (only a constant is fitted to all parameters) and L(fitted) is the current fitted model. This definition sometimes is referred to as the Cox & Snell R-squared. The Nagelkerke /Cragg & Uhler's definition divides the above with
1-L(0)^(2/n)
The Rsq() produces a single value if type="Cox Snell" or "Cragg Uhler" and a list if type="both".
The null model is fitted using the function gamlssML() which can create warning messages
Mikis Stasinopoulos d.stasinopoulos@londonmet.ac.uk
Nagelkerke, N. J. (1991). A note on a general definition of the coefficient of determination. Biometrika, 78(3), 691-692.
Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.
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, https://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 https://www.gamlss.com/).
data(aids) m1 <- gamlss(y~x+qrt, data=aids, family=NBI) Rsq(m1) Rsq(m1, type="both")
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