[Biomod-commits] Using independent data to evaluate a model

[Gildenhuys, E, Mej <egil@sun.ac.za>]

Thank you for the quick response Damien. I understand what you mean about the coordinates now.



Regarding the error I did what you proposed do to, but I'm still getting the same error. I think I cleaned my data rather well and I'm able to model both these datasets successfully when I don't use independent data. Is there perhaps another package that I should load into my library that I am unaware of?



Many thanx





Enelge Gildenhuys
MSc student
Department of Botany & Zoology
Centre of Excellence for Invasion Biology
Universiteit Stellenbosch University

________________________________
From: Damien Georges [damien.georges2 at gmail.com]
Sent: 26 October 2012 03:08 PM
To: biomod-commits at lists.r-forge.r-project.org; Gildenhuys, E, Mej <egil at sun.ac.za>
Subject: Re: [Biomod-commits] Using independent data to evaluate a model

Dear Enelge,

First of all, you have to know that an updated version of BIOMOD package called biomod2 is able on R-Forge since a while. I strongly encourage you to switch to this package version if you just began your study.

That being said, all models developed in BIOMOD (the version you are working with) are not spacial based models (they don't need points coordinates to work) so you don't have to give such information for your independent data. For "calibrating data", the coordinates are optional and only used for results plotting.

Concerning the error you have.. could you check first that no NA's occurs in your dataset.

## Check if some NA's occurs
summary(alldata5)
summary(alldataH)

## If some NA's.. do someting like
alldata5 <- na.omit(alldata5)
alldataH <- na.omit(alldataH)
## and run your script again..

Does it helps?

Best,

Damien

On 26/10/2012 13:12, Gildenhuys, E, Mej <egil at sun.ac.za><mailto:egil at sun.ac.za> wrote:
Good day,

I hope this email finds you well. I am currently trying to evaluate my species modelling using independent data. I have followed the tutorial and manual, however, in the manual the same data is used for the independent data as the modelling data and consequently has the same name, where they differ in mine. The problem is that I do not know where/how to read in the coordinates of my independent data from which my model will be evaluated. I suppose in the tutorial example there is no need to read it in twice as it has the same name?

Initial.State(Response = alldata5[,1], Explanatory = alldata5[,2:7], IndependentResponse = alldataH[,1], IndependentExplanatory = alldataH[,2:7], sp.name="halicacabum")
ls()
Models(GBM = T, No.trees = 2000,
       NbRepPA=2,
       strategy="random",
       coor=alldata5[,8:9],
       nb.absences=10000,
       DataSplit = 70,
       NbRunEval = 4,
       KeepPredIndependent=T,
       Roc = T,
       Optimized.Threshold.Roc=T,
       TSS=T,
       VarImport=T
)


If I run this model I get the following error:


-----------------------------------
Modelling summary
-----------------------------------
Number of species modelled :          1
halicacabum

numerical variables :                 mtcoldm, mtwarmm, pcoldq, pdrym, pwarmq, ts


number of evaluation repetitions :    4
number of pseudo-absences runs :      2
models selected :                     GBM
total number of model runs :          10
-----------------------------------


#####                  halicacabum                   #####
#####             pseudo-absence run 1                       #####
Model=Generalised Boosting Regression
         2000 maximum different trees and lambda Fold Cross-Validation
Error in TSS.Stat(Misc) : subscript out of bounds
In addition: Warning message:
In rbind(Misc, a) :
  number of columns of result is not a multiple of vector length (arg 1)


Thanx!

Enelge




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