Re: [R] gamlss results for EXP and LNO seem to have reversed AIC scores

Global Deviance = -2*fitted log likelihood, AIC = Global deviance +2*number of parameters Choocing distribution with the lowest AIC selects the exponential -- View this message in context: http://r.789695.n4.nabble.com/gamlss-results-for-EXP-and-LNO-seem-to-have-reversed-AIC-scores-tp4409754p4496

Re: [R] gamlss results for EXP and LNO seem to have reversed AIC scores

Thank you. I was obviously mis-interpreting the AIC results. RdR -- View this message in context: http://r.789695.n4.nabble.com/gamlss-results-for-EXP-and-LNO-seem-to-have-reversed-AIC-scores-tp4413702p4415275.html Sent from the R help mailing list archive at Nabble.com. __

[R] gamlss results for EXP and LNO seem to have reversed AIC scores

Dear Richard I think the results below are consistent set.seed(1020) # created from EXP X1 <- rEXP(1000) Gexp <- gamlss(X1~1,family=EXP) #GAMLSS-RS iteration 1: Global Deviance = 1999.762 #GAMLSS-RS iteration 2: Global Deviance = 1999.762 Glno <- gamlss(X1~1,family=LOGNO) #GAMLSS-RS iterat

[R] gamlss results for EXP and LNO seem to have reversed AIC scores

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 iterat