[R-sig-eco] GLS - Plotting Graphs with 95% conf interval

[Chris Howden]

Hi sam,

I'm not familiar with the function with gls so can't help u with
that.. But if u get no joy on this list there is a mixed effects list
called r-sig-me.

Chris Howden
Founding Partner
Tricky Solutions
Tricky Solutions 4 Tricky Problems
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Innovation, Data Analysis, Modelling and Training

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On 12/07/2011, at 2:02, "Cox, Samantha Lucy" <s.cox.10 at aberdeen.ac.uk> wrote:

> Hi, I am new to this group.  Firstly I am just wondering if there is a search option to look through back dated achrives (rather than having to mannually sift through all the threads by month)?
>
>
>
> Secondly (and the subject of this post) I am trying to plot the original data with the line of the model using the predict function.  I want to add SE to the graph, but not sure how to get them out as the predict function for gls (package nlme) does not appear to allow for SE=TRUE argument.
>
> Here is my code so far:
>
> f1<-formula(MaxNASC40_50~hu3+flcmax+TidalFlag)
>
> vf1Exp<-varExp(form=~hu3)
>
> B1D<-gls(f1,correlation=corGaus(form=Lat~Lon, nugget=TRUE),weights=vf1Exp , data=ocean)
>
> ochu3<-seq(from=2.9,to=4,length=120)
> ocflc<-seq(from=0,to=0.8,length=120)
> tidal1<-rep(c("1"),length=120)
>
> mydata1<-data.frame(TidalFlag=factor(tidal1),hu3=ochu3,flcmax=ocflc)
> lineNASC1<-predict(B1D,newdata=mydata1,type="response")
> lineNASC1<-as.data.frame(lineNASC1)
>
> plot(ocean$MaxNASC40_50[ocean$TidalFlag==1]~ocean$flcmax[ocean$TidalFlag==1)
> lines(lineNASC1$lineNASC1~mydata1$flcmax)
>
> Tidal Flag is a factor (so i assume i have to plot seperate graphs for each level).
>
> When I have tried to use the effects package I get the error:  Error in x$formula : object of type 'symbol' is not subsettable.
>
> Also (regarding plotting but a different modelling framework) when i have been trying to predict values from a zero inflated negative binomial (package pscl), I am getting the same line of fit regardless of what is on my X axis (depsite different variables have positive and negative relationships).
>
> any imput on any of these problems would be appreciated.
>
> Thanks
>
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>
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