Hi,

I'm a bit puzzled by the gamlss fitting of exponential and lognormal data. 
Gamlss seems 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

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