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...s to think that exponentially distributed data fits better with a lognormal distribution, and vice versa. For example, X <- rexp(1000) Gexp <- gamlss(X~1,family=EXP) # X~1 is X tilde 1 GAMLSS-RS iteration 1: Global Deviance = 2037.825 GAMLSS-RS iteration 2: Global Deviance = 2037.825 Glno <- gamlss(X~1,family=LNO) GAMLSS-RS iteration 1: Global Deviance = 2185.763 GAMLSS-RS iteration 2: Global Deviance = 2185.763 Gexp$aic [1] 2039.825 Glno$aic [1] 2189.763 Can anybody shed light on why these results would occur? cheers, RdR -- View this message in context: http://r.789695...

...lar results on repeated trials and with Normal and standard normal distributions. How should I understand sigma in these results? cheers, RdR ######### Example ######### # enable reproduction set.seed(1234) # create some lognormal data X <- rlnorm(1000,meanlog=10,sdlog=2) # try gamlss fit gLNO <- gamlss(X~1,family=LNO) summary(gLNO) ******************************************************************* Family: c("LNO", "Box-Cox") Call: gamlss(formula = X ~ 1, family = LNO) Fitting method: RS() -----------------------------------------------------------------...