Error while running ENMEVAL in R

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arjun nepal

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Jul 9, 2021, 9:15:26 AM7/9/21
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Dear all,
i am running ENMeval for hornbill in one district in Bhutan. i could develop bias file and could get potential points as well. 

The problem came while running this particular codes and i am not able to figure it out. 

CODES
enmeval_results <- ENMevaluate(occ, env, method="randomkfold",Kfold= 10, 
                               algorithm='maxent.jar', bg.coords = bg)
Error message 
Error in ENMevaluate(occ, env, method = "randomkfold", Kfold = 10, algorithm = "maxent.jar",  : 
  unused argument (Kfold = 10)

Thank you in advance 

gafna jeff

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Jul 9, 2021, 10:11:38 AM7/9/21
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Hello,

The error is telling you that you are using the wrong argument. Try this " kfolds =10" and not Kfold=10

  method="randomkfold", kfolds=10


Hope it works for you

Jeff




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arjun nepal

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Jul 9, 2021, 10:54:11 AM7/9/21
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Thank you Jeff 
It worked 
Take care
Regards

gafna jeff

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Jul 9, 2021, 11:40:16 AM7/9/21
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Sunil Sapkota

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Dec 8, 2021, 2:12:06 AM12/8/21
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Code: enmeval_results <- ENMevaluate(occ, env, method="randomkfold", kfolds = 10, categoricals=c(10), algorithm='maxent.jar', bg.coords = bg)

Error message:  ENMevaluate(occ, env, method = "randomkfold", kfolds = 10, categoricals = c(10),  :
  unused argument (kfolds = 10)

Sunil Sapkota

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Dec 8, 2021, 3:07:17 AM12/8/21
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Dear all, 

any solution for this issue please suggest . 

> enmeval_results <- ENMevaluate(occ, env, method="randomkfold", "kfolds = 10", categoricals= 10, algorithm='maxnet', bg.coords = bg)
* Running ENMeval v2.0.0 with legacy arguments. These will be phased out in the next version.
*** Running initial checks... ***

Error in enm@errors(occs, envs, bg, tune.args, partitions, algorithm,  :
  Maxent settings must include 'rm' (regularization multiplier) and 'fc' (feature class) settings. See ?tune.args for details

Ione Arbilla

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Dec 8, 2021, 3:12:50 AM12/8/21
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Hello Suni,
 You need to include the regularization multiplier argument (rm) and the features classes (fc) that you want to include in your models.  For example:


e.mx <- ENMevaluate(occs = occs, envs = envs, bg = bg, 
                    algorithm = 'maxnet', partitions = 'block', 
                    tune.args = list(fc = c("L","LQ","LQH","H"), rm = 1:5))

The vignette is very useful;
https://jamiemkass.github.io/ENMeval/articles/ENMeval-2.0.0-vignette.html#running-enmeval

Cheers,


Ione


Sunil Sapkota

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Jan 26, 2022, 6:52:24 AM1/26/22
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thank you 
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