[R] predicted values after fitting gamma2 function

[David Winsemius]

On Jun 25, 2009, at 11:30 PM, Steven Matthew Anderson wrote:

> Question: after fitting a gamma function to some data, how do I get  
> predicted values?  I'm a SAS programmer, I new R, and am having  
> problems getting my brain to function with the concept of "object as  
> class ...".  The following is specifics of what I am doing:
>
> I'm trying to determine the pdf from data I have created in a  
> simulation.
> I have generated frequency counts using the following:
>
>  Max.brks <- pretty(range(Max.Spread$Distance), 100)
>  Max.f<-hist(x=Max.Spread$Distance,
>               breaks=Max.brks,plot=FALSE )
>  Max.cnt<-as.data.frame(cbind(sim,Max.f$mids,Max.f$counts))
>  colnames(Max.cnt)<-c("Simulation","MidPoint","Count")
>
> then I fit this to a gamma distribution function:

Using a non-base function without including the appropriate require()  
or library() call is a bit like asking a SAS programmer to debug code  
but not telling what PROC it's from;

>  modl<- 
> vglm 
> (Count 
> ~ 
> MidPoint 
> ,gamma2 
> ,data 
> = 
> subset(Max.cnt,select=(simulation,MidPoint,Count),trace=TRUE,crit="c")
>  print(coef(modl2,matrix=TRUE))
>  print(summary(modl2))
>
> This produces the output:
>
snipped output
>
>
> Now - how do I get this information to give me predicted values  
> given the same x-values I used in the experimental model (i.e. from  
> Max.brks <- pretty(range(Max.Spread$Distance), 100)).

Most regression functions in R, and vglm is no exception, have predict  
methods. The default is to give back predictions for the data from  
which the parameters were estimated, but if you want predictions on  
specific new values there is a newdata option.

?predict.vglm


David Winsemius, MD
Heritage Laboratories
West Hartford, CT