Hi Folks!  Just started using the gamlss package and I tried a simple code
example (see below).  Why the negative sigma?

John


> y <- rt(100, df=1)> m1<-fitDist(y, type="realline")Warning messages:1: In MLE(ll3, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma,  :
  possible convergence problem: optim gave code=1 false convergence
(8)2: In MLE(ll4, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma,
 :
  possible convergence problem: optim gave code=1 false convergence
(8)3: In MLE(ll4, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma,
 :
  possible convergence problem: optim gave code=1 false convergence
(8)4: In MLE(ll4, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma,
 :
  possible convergence problem: optim gave code=1 false convergence
(8)5: In MLE(ll4, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma,
 :
  possible convergence problem: optim gave code=1 false convergence (8)> > m1
Family:  c("TF", "t Family")
Fitting method: "nlminb"

Call:  gamlssML(y = y, family = DIST[i])

Mu Coefficients:
[1]  0.2376
Sigma Coefficients:
[1]  -0.09865
Nu Coefficients:
[1]  -0.2281

 Degrees of Freedom for the fit: 3 Residual Deg. of Freedom   97
Global Deviance:     545.069
            AIC:     551.069
            SBC:     558.885


Another draw:


> y <- rt(100, df=1)> m1<-fitDist(y, type="realline")Warning messages:1: In MLE(ll3, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma,  :
  possible convergence problem: optim gave code=1 false convergence
(8)2: In MLE(ll4, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma,
 :
  possible convergence problem: optim gave code=1 false convergence
(8)3: In MLE(ll4, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma,
 :
  possible convergence problem: optim gave code=1 false convergence
(8)4: In MLE(ll4, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma,
 :
  possible convergence problem: optim gave code=1 false convergence
(8)5: In MLE(ll4, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma,
 :
  possible convergence problem: optim gave code=1 false convergence (8)> > m1
Family:  c("ST1", "Skew t (Azzalini type 1)")
Fitting method: "nlminb"

Call:  gamlssML(y = y, family = DIST[i])

Mu Coefficients:
[1]  -0.05249
Sigma Coefficients:
[1]  -0.1545
Nu Coefficients:
[1]  0.04445
Tau Coefficients:
[1]  -0.1352

 Degrees of Freedom for the fit: 4 Residual Deg. of Freedom   96
Global Deviance:     505.414
            AIC:     513.414
            SBC:     523.835



> sessionInfo()R version 2.15.1 (2012-06-22)
Platform: x86_64-pc-mingw32/x64 (64-bit)

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United
States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United
States.1252

attached base packages:
[1] splines   stats     graphics  grDevices utils     datasets
methods   base

other attached packages:
[1] gamlss_4.1-8      gamlss.data_4.1-0 gamlss.dist_4.1-6 nlme_3.1-104
     MASS_7.3-21

loaded via a namespace (and not attached):
[1] grid_2.15.1      lattice_0.20-10  survival_2.36-14 tools_2.15.1

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