R help - May 2011 - Linear Discriminant Analysis error: "Variables appear constant"

Hi R experts,

I'm attempting to run Linear Discriminant Analysis using the lda function in
the MASS package. I've got around 50 predictor variables and one response
variable. My response variable has 5 numeric categories that represent different
clusters of fish abundance data (clusters were developed using Bray-Curtis and
NMDS), and my predictor variables are environmental variables that might
influence the fish data. These data all came from 68 sampling locations.

I'm getting an error message:
>DALogFish<-lda(Cluster~DrainArea+Flow+StrmWidth+Gradient+NatComm+FishIBIUsed
+QHEI+QHEIsub+QHEImwh_h+QHEIcov+QHEIchan+QHEIrip+QHEIpool+QHEIrif+QHEIgrads+
QHEIgradv+QHEImwh+QHEIcovtype+QHEIwwh+QHab+QHabBuff+QHabEros+QhabPool+
QHabWDRatio+QHabRif+QHabFines+QHabCov+QHabRating+QHabSize+TP+TKN+NH3+NH3Min
+NO3NO2N+BOD+TSS+TSSMax+TDS+SSC+SSCMax+Chloride+Sulfate+Ecoli+ChlA+DOper+
DOperMin+DOperMin1_5+DOmgL+DOmgLMean+DOmgLMax+Cond+pH+pHMax+Trans+Temp+
TempMin+Temp4+Crop100+Crop500+CropSub+Dev100+Dev500+DevSub+For100+For500+
ForSub+Pas100+Pas500+PasSub+Wat100+Wat500+WatSub+Wet100+Wet500+WetSub+
Undev100+Undev500+UndevTotal+Undev100NoPas+Undev500NoPas+UndevTotNoPas,
data=AllData1, na.action="na.omit", CV=TRUE)

Error in lda.default(x, grouping, ...) :
  variables 10 38 42 appear to be constant within groups

When I look at the variables listed, they don't appear "constant within
the groups" to me. I'm new to LDA and am wondering what this error
means... Are my data somehow not in the right format? Should I remove colinear
variables? (All variables have been normalized.)

Thanks very much!
Katie



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On 16.05.2011 22:07, Songer, Katherine B - DNR wrote:
> Hi R experts,
>
> I'm attempting to run Linear Discriminant Analysis using the lda
function in the MASS package. I've got around 50 predictor variables and one
response variable. My response variable has 5 numeric categories that represent
different clusters of fish abundance data (clusters were developed using
Bray-Curtis and NMDS), and my predictor variables are environmental variables
that might influence the fish data. These data all came from 68 sampling
locations.
>
> I'm getting an error message:
>
>>
DALogFish<-lda(Cluster~DrainArea+Flow+StrmWidth+Gradient+NatComm+FishIBIUsed
>
+QHEI+QHEIsub+QHEImwh_h+QHEIcov+QHEIchan+QHEIrip+QHEIpool+QHEIrif+QHEIgrads+
> QHEIgradv+QHEImwh+QHEIcovtype+QHEIwwh+QHab+QHabBuff+QHabEros+QhabPool+
> QHabWDRatio+QHabRif+QHabFines+QHabCov+QHabRating+QHabSize+TP+TKN+NH3+NH3Min
> +NO3NO2N+BOD+TSS+TSSMax+TDS+SSC+SSCMax+Chloride+Sulfate+Ecoli+ChlA+DOper+
> DOperMin+DOperMin1_5+DOmgL+DOmgLMean+DOmgLMax+Cond+pH+pHMax+Trans+Temp+
> TempMin+Temp4+Crop100+Crop500+CropSub+Dev100+Dev500+DevSub+For100+For500+
> ForSub+Pas100+Pas500+PasSub+Wat100+Wat500+WatSub+Wet100+Wet500+WetSub+
> Undev100+Undev500+UndevTotal+Undev100NoPas+Undev500NoPas+UndevTotNoPas,
> data=AllData1, na.action="na.omit", CV=TRUE)
>
> Error in lda.default(x, grouping, ...) :
>    variables 10 38 42 appear to be constant within groups
>
> When I look at the variables listed, they don't appear "constant
within the groups" to me.
We do not know, since we do not have the data.

>I'm new to LDA and am wondering what this error means... Are my data
somehow not in the right format? Should I remove colinear variables? (All
variables have been normalized.)
Yes, colinear variables should be removed. Note als, that you have 
roughly as many (or even more) variables in the model than observations. 
This won't work either. I think you should read some textbook on the 
mechanisms behind an LDA.

Uwe Ligges

>
> Thanks very much!
> Katie
>
>
>
> 	[[alternative HTML version deleted]]
>
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