Forum: biomod2 package is now available !
Posted by: damien georges
Content: Dear BIOMOD-users,You were eagerly waiting for it, and we are happy to say that the new version of BIOMOD called biomod2 is now online on R-Forge. Although we kept the same modelling philosophy than the former version (which we will still maintain for a while), we have made crucial changes. biomod2 is now fully object-oriented and made for running on a single species only (see vignette MultiSpeciesModelling for multi-species modelling at once). For advanced BIOMOD users, the new functions might be a bit disturbing at the beginning. Then, you will see that this new version is much more advanced and practical than the former ones. Among the novelties, the addition of MAXENT in the modelling techniques, a large range of evaluation metrics, a more refined definition of ensemble modelling and ensemble forecasting, the possibility to give presence-only data and environmental rasters to biomod2 and let it extract pseudo-absence data directly. We have created several vignettes for you to get use to this new version and a figure explaining the different ways of giving data to BIOMOD. Please bear in mind that R-Forge is a development platform, it means that this new package would experience repeated updating the next couple of weeks (correcting bugs, adding documentation, adding functionalities) so think about updating the package before each new study you will do. Last but not least, all comments are welcome! If you find a bug, if you think some documentation points are unclear, if you think about new functionalities that may be useful, just let us know ASAP. We count on you to help finalizing this new version to a very nice tool. We will then release it to CRAN by the end of July. Please remember to add your code, R-version, OS and BIOMOD-version every time you report a bug or a mistake in the vignette or help files. Hoping you will enjoy this new version of BIOMOD. With our best wishes, Damien & Wilfried |
Latest Newsbiomod2 is now devel on githubdamien georges - 2020-03-02 17:08 -
biomod2 package is now available !damien georges - 2012-07-26 13:56 -
...
|
Monitor Forum | 
Start New Thread
| RE: SWD background MAXENT [ Reply ] By: damien georges on 2016-10-19 10:17 | [forum:43567] |
|
Dear Marta, I think that the way you are using biomod2 is perfectly find here.. I would maybe just turn off the option rescal.all.models (rescal.all.models = FALSE). What is your concern about the results? Do they look good/bad? What you can do is to run couple of other models (e.g. GLM, RF, ...) in the mean time to compare visually the models output and see if all this projection are more or less similar. Cheers, Damien |
|
| SWD background MAXENT [ Reply ] By: Marta TobMor on 2016-08-22 13:10 | [forum:43565] |
|
Hi everyone, I'm using Biomod2 to calculate the TSS of my maxent models. But I'm not sure, it's the models are build with all my background points selected. Because I tried to used this script, but the results are suspicious amazing! I have my database in this format: Sp , Var1 , Var 2, X, Y BAC D N3xStd X_dd_LONG Y_dd_LAT 1 -1222 0 -30.21720 38.28660 1 -1286 0 -27.85769 39.20803 ## script resp.name="BAC" bmData <- BIOMOD_FormatingData(resp.var = as.numeric(tssDB[,myRespName]), resp.xy = tssDB[,4:5], resp.name="BAC", expl.var = tssDB[,2:3], PA.nb.rep=1,PA.nb.absences = 10000, PA.strategy = 'disk',PA.dist.min = 0,PA.dist.max = NULL,na.rm=TRUE)#,PA.strategy = 'user.defined') bmData# it shows the exactly number of presences and undifined (background) # myBioOption <- BIOMOD_ModelingOptions() #BAC MAXENT = list( path_to_maxent.jar = 'C:/Users/rprieto/Documents/lixo/', memory_allocated = 2024,maximumiterations =5000, visible = FALSE, linear = TRUE, quadratic = TRUE, product = FALSE, threshold = FALSE, hinge = FALSE, lq2lqptthreshold = 80, l2lqthreshold = 10, hingethreshold = 15, beta_threshold = -1, beta_categorical = -1, beta_lqp = -1, beta_hinge = -1, defaultprevalence = 0.5) MAXENT # myBacSWDModelOut <- BIOMOD_Modeling(bmData,models = c('MAXENT'),models.options = myBioOption,NbRunEval=10,DataSplit=90,Yweights=NULL,models.eval.meth = c('TSS','ROC'),SaveObj = TRUE,rescal.all.models = TRUE)# Prevalence=0.5, VarImport=3, Thanks in advance Marta |
|
