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: Chosing treashold [ Reply ] By: Wilfried Thuiller on 2017-08-30 14:49 | [forum:45302] |
|
Dear Camila, Since I guess the prevalence of your species are different, I would rather chose the best threshold for each species individually. Best Wilfried |
|
| Chosing treashold [ Reply ] By: Camila Neder on 2017-08-30 14:45 | [forum:45301] |
|
Dear all, Probably is a simple question, but I would like to have your opinion. I am modeling different species distribution, and since I want to make the final ensemble model comparable, I have to run them equally. Am I correct,isn't? So, I have this dutty: When I run the 9 algorithms available (all excluding MAXENT) for sp1 I have evaluation values of TSS in a range from 0.4-0.7; then for sp2 from 0.75-0.97. If I chose a treashold of 0.65 to have a Good quality EM, for sp2 all models will be included. What do you think better, to chose a higher treashold value to have a better model for sp2? Or this will cancell the comparison between the EM of two different species distribution? On an other hand, for sp1 only GBM and RF are included. This single algorithms work better for both species and extra one for sp1-GLM- and for sp2 -ANN-. If I model the distribution using less algorithm than the 9 before, I have higher evaluation values. But then, how can I deal with this difference? Because if I model with GBM,RF and GLM for sp1 and GBM,RF and ANN for sp2 I will make no-comparable models. Which could be the best strategy? Hope making myself undestandable with the questions. THANKS IN ADVANCE!! Cami |
|
