On Jan 23, 2013, at 12:14 PM, Katherine Gobin wrote:
> Dear R helpers,
>
> I have following loss data and I need to fit LEFT truncated Log Normal
> distribution to this data which is Truncated at 1000000.
>
> dat =
> c(1333834,5710254,9987567,7809469,6940935,3473671,1270209,1102523,1124002,
> 5830159,4302300,3925242,2638409,2324421,7238436,9088709,7439250,4976551,4864319,
> 8741334,1863770,7098310,4942288,4971829,4986372)
>
> library(gamlss.tr)
>
> gen.trun(5, LOGNO)
>
> result <- gamlss(dat~1, family=LOGNOtr)
>
>
> # THIS GIVES
>
>> result
>
> Family: c("LOGNOtr", "left truncated Log Normal")
>
> Fitting method: RS()
>
> Call: gamlss(formula = dat ~ 1, family = LOGNOtr)
>
> Mu Coefficients:
> (Intercept)
> 15.23
> Sigma Coefficients:
> (Intercept)
> -0.3977
>
> Degrees of Freedom for the fit: 2 Residual Deg. of Freedom 23
> Global Deviance: 812.568
> AIC: 816.568
> SBC: 819.006
>
> My problem is how do I extract these values of Mu Coefficients and Sigma
> Coefficients, if I want to use these values for further analyses?
After looking at names(result)
> result$mu.coefficients
(Intercept)
15.23012
> result$sigma.coefficients
(Intercept)
-0.3976947
> help(gamlss.tr)
I looked for an extractor function in hte Index for htat package but didn't
find one. Since this is a suite of packages you should probably do your own
more extensive search in the documents.
--
David
David Winsemius
Alameda, CA, USA
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