Re: [R] code ok in unix & R2.6 , fails in windows & R 2.12

2012-10-16 Thread Jellevanloon
Hi,

I'm experiencing the same problems.. Installed the package DRM yestarday..
first couple of runs it worked..
I closed down R and now I want to do the same code again and I get the
error:

Error in drm(TotDmShoot ~ DAP, data = DATA, fct = gompGrowth.2()) : 
  Cluster not specified. Use e.g. y ~ x + cluster(id)

What do I have to do to fix this? 

Thank you,

Jelle



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Re: [R] code ok in unix & R2.6 , fails in windows & R 2.12

2011-02-08 Thread Ramya

Hi there,

I am using R version 2-12.1 and I am trying to use drm functions which is
version 0.5-8 both are the latest versions. 

but still it get the same Error  drm(Response ~ Expected, data = SC, fct =
LL.4()) : 
  Cluster not specified. Use e.g. y ~ x + cluster(id)

Any help would be of much help.

my data 

> SC <- read.delim("/Users/Ramya/d1.txt")
> SC
  Response Expected
1 10.06235500.0
2 16.62795250.0
3 28.79325125.0
4 44.03961 62.5
5 60.19685 31.3
6 77.03876 15.6
7 80.17484  7.8
8 82.66292  3.9
> FourP <- drm(Response~Expected, data = SC, fct = LL.4())
Error in drm(Response ~ Expected, data = SC, fct = LL.4()) : 
  Cluster not specified. Use e.g. y ~ x + cluster(id)

Thanks
Ramya
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Re: [R] code ok in unix & R2.6 , fails in windows & R 2.12

2010-11-09 Thread Robert Kinley
apologies for omitting the data 


   conc  response curve
150 0.7533954 1
250 0.7755960 2
350 0.8001151 3
489 0.2858031 1
589 0.2883478 2
689 0.2954936 3
7   158 0.4296482 1
8   158 0.4406220 2
9   158 0.4567403 3
10  282 0.6484347 1
11  282 0.6555722 2
12  282 0.7361552 3
13  501 0.9768917 1
14  501 0.9809505 2
15  501 0.9952711 3
16  890 1.395 1
17  890 1.3262830 2
18  890 1.4754281 3
19 1582 2.2157078 1
20 1582 2.2918927 2
21 1582 2.5538562 3
22 2813 3.7403291 1
23 2813 4.0623972 2
24 2813 4.1439147 3
25 5000 5.1405423 1
26 5000 5.4242582 2
27 5000 5.4322730 3

also -

> model
[[1]]

A 'drc' model.

Call:
drm(formula = response ~ conc, data = assay.data, fct = l4())

Coefficients:
b:(Intercept)  c:(Intercept)  d:(Intercept)  e:(Intercept) 
  -1.6958 0.5089 6.9764  2629.7526 


attr(,"logScale")
[1] TRUE
attr(,"modelType")
[1] "4pl"
attr(,"method")
[1] "drc"
attr(,"class")
[1] "multFit"





Uwe Ligges  
09/11/2010 16:21

To
Robert Kinley 
cc
r-help@r-project.org
Subject
Re: [R] code ok in unix & R2.6 , fails in windows & R 2.12






We cannot help since we do not have the data.

Uwe


On 09.11.2010 16:40, Robert Kinley wrote:
> hello ...
>
> Can anyone help me with this :
>
>
> In R.exe 2.6 , Unix , :-
>
> plot.data<-model[[i]]$data$conc
> newdata<-seq(min(plot.data),max(plot.data),by=1)
> 
model.pred<-predict(model[[i]],data.frame(newdata),interval="prediction")
> matpoints(newdata,model.pred[,c("Lower","Upper")],"l",col="blue",lty=1)
>
> works OK ...
>
>
> in Rgui  2.12 , Windows XP , same code
>
>> plot.data<-model[[i]]$data$conc
>> newdata<-seq(min(plot.data),max(plot.data),by=1)
>>
> 
model.pred<-predict(model[[i]],data.frame(newdata),interval="prediction")
> Error in `[.data.frame`(newdata, , 2) : undefined columns selected
>
>
>
>Robert Kinley  ( 'baffled' of Berkshire )
>
>
>
>[[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide 
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.


[[alternative HTML version deleted]]

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Re: [R] code ok in unix & R2.6 , fails in windows & R 2.12

2010-11-09 Thread Uwe Ligges

We cannot help since we do not have the data.

Uwe


On 09.11.2010 16:40, Robert Kinley wrote:

hello ...

Can anyone help me with this :


In R.exe 2.6 , Unix , :-

plot.data<-model[[i]]$data$conc
newdata<-seq(min(plot.data),max(plot.data),by=1)
model.pred<-predict(model[[i]],data.frame(newdata),interval="prediction")
matpoints(newdata,model.pred[,c("Lower","Upper")],"l",col="blue",lty=1)

works OK ...


in Rgui  2.12 , Windows XP , same code


plot.data<-model[[i]]$data$conc
newdata<-seq(min(plot.data),max(plot.data),by=1)


model.pred<-predict(model[[i]],data.frame(newdata),interval="prediction")
Error in `[.data.frame`(newdata, , 2) : undefined columns selected



   Robert Kinley  ( 'baffled' of Berkshire )



[[alternative HTML version deleted]]

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and provide commented, minimal, self-contained, reproducible code.


__
R-help@r-project.org mailing list
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Re: [R] code ok in unix & R2.6 , fails in windows & R 2.12

2010-11-09 Thread Uwe Ligges
You probably forgot to say that you have also different versions of the 
package installed!


I get on all platforms:

> drm(formula = response ~ conc, data = assay.data, fct = l4())
Error in drm(formula = response ~ conc, data = assay.data, fct = l4()) :
  Cluster not specified. Use e.g. y ~ x + cluster(id)


with recent versions of R and drm.


So time to update R and all your packages on all your platforms.

Best,
Uwe Ligges



On 09.11.2010 17:26, Robert Kinley wrote:


apologies for omitting the data 


conc response curve
1 50 0.7533954 1
2 50 0.7755960 2
3 50 0.8001151 3
4 89 0.2858031 1
5 89 0.2883478 2
6 89 0.2954936 3
7 158 0.4296482 1
8 158 0.4406220 2
9 158 0.4567403 3
10 282 0.6484347 1
11 282 0.6555722 2
12 282 0.7361552 3
13 501 0.9768917 1
14 501 0.9809505 2
15 501 0.9952711 3
16 890 1.395 1
17 890 1.3262830 2
18 890 1.4754281 3
19 1582 2.2157078 1
20 1582 2.2918927 2
21 1582 2.5538562 3
22 2813 3.7403291 1
23 2813 4.0623972 2
24 2813 4.1439147 3
25 5000 5.1405423 1
26 5000 5.4242582 2
27 5000 5.4322730 3

also -

 > model
[[1]]

A 'drc' model.

Call:
drm(formula = response ~ conc, data = assay.data, fct = l4())

Coefficients:
b:(Intercept) c:(Intercept) d:(Intercept) e:(Intercept)
-1.6958 0.5089 6.9764 2629.7526


attr(,"logScale")
[1] TRUE
attr(,"modelType")
[1] "4pl"
attr(,"method")
[1] "drc"
attr(,"class")
[1] "multFit"




*Uwe Ligges *

09/11/2010 16:21

        
To
    Robert Kinley 
cc
    r-help@r-project.org
Subject
Re: [R] code ok in unix & R2.6 , fails in windows & R 2.12








We cannot help since we do not have the data.

Uwe


On 09.11.2010 16:40, Robert Kinley wrote:
 > hello ...
 >
 > Can anyone help me with this :
 >
 >
 > In R.exe 2.6 , Unix , :-
 >
 > plot.data<-model[[i]]$data$conc
 > newdata<-seq(min(plot.data),max(plot.data),by=1)
 > model.pred<-predict(model[[i]],data.frame(newdata),interval="prediction")
 > matpoints(newdata,model.pred[,c("Lower","Upper")],"l",col="blue",lty=1)
 >
 > works OK ...
 >
 >
 > in Rgui 2.12 , Windows XP , same code
 >
 >> plot.data<-model[[i]]$data$conc
 >> newdata<-seq(min(plot.data),max(plot.data),by=1)
 >>
 > model.pred<-predict(model[[i]],data.frame(newdata),interval="prediction")
 > Error in `[.data.frame`(newdata, , 2) : undefined columns selected
 >
 >
 >
 > Robert Kinley ( 'baffled' of Berkshire )
 >
 >
 >
 > [[alternative HTML version deleted]]
 >
 > __
 > R-help@r-project.org mailing list
 > https://stat.ethz.ch/mailman/listinfo/r-help
 > PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
 > and provide commented, minimal, self-contained, reproducible code.



__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


[R] code ok in unix & R2.6 , fails in windows & R 2.12

2010-11-09 Thread Robert Kinley
hello ...

Can anyone help me with this :


In R.exe 2.6 , Unix , :-

plot.data<-model[[i]]$data$conc
newdata<-seq(min(plot.data),max(plot.data),by=1)
model.pred<-predict(model[[i]],data.frame(newdata),interval="prediction")
matpoints(newdata,model.pred[,c("Lower","Upper")],"l",col="blue",lty=1)

works OK ... 


in Rgui  2.12 , Windows XP , same code 

> plot.data<-model[[i]]$data$conc
> newdata<-seq(min(plot.data),max(plot.data),by=1)
> 
model.pred<-predict(model[[i]],data.frame(newdata),interval="prediction")
Error in `[.data.frame`(newdata, , 2) : undefined columns selected
 
 

  Robert Kinley  ( 'baffled' of Berkshire )
 
 

[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list
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and provide commented, minimal, self-contained, reproducible code.