Hi all,

I'm trying to port some niche modeling methodology to R, and to convince
myself that I have succeeded, I am trying to produce identical results with
the stand-alone Maxent application and with Maxent run through the Dismo R
package. However, despite my best efforts to use the exact same options,
occurrence points and environmental rasters, the results are not identical.
I have posted the output from both approaches. From the "command line to
repeat" section, it looks like I am using the exact same options. But there
are differences in training gain, and in the lambdas file (which is
important for me because I am using the lambdas file to get a count of
parameters). Does anyone have any ideas as to why I don't get identical
results?

Here is the output from Maxent stand-alone:

*Regularized training gain is 3.821, training AUC is 0.997, unregularized
training gain is 4.509.
Algorithm terminated after 500 iterations (6 seconds).

The follow settings were used during the run:
28 presence records used for training.
10000 points used to determine the Maxent distribution (background points).
Environmental layers used (all continuous): bio1 bio10 bio11 bio12 bio13
bio14 bio15 bio16 bio17 bio18 bio19 bio2 bio3 bio4 bio5 bio6 bio7 bio8 bio9
Regularization values: linear/quadratic/product: 0.288, categorical: 0.250,
threshold: 1.720, hinge: 0.500
Feature types used: linear quadratic hinge
outputformat: raw
outputdirectory: /Users/Pascal/Desktop/sdmtools/results/beta1
samplesfile: /Users/Pascal/Desktop/sdmtools/occ.csv
environmentallayers: /Users/Pascal/Desktop/sdmtools
removeduplicates: false
addsamplestobackground: false
Command line used:

Command line to repeat this species model: java density.MaxEnt nowarnings
noprefixes -E "" -E sp outputformat=raw
outputdirectory=/Users/Pascal/Desktop/sdmtools/results/beta1
samplesfile=/Users/Pascal/Desktop/sdmtools/occ.csv
environmentallayers=/Users/Pascal/Desktop/sdmtools noremoveduplicates
noaddsamplestobackground*
*
*
And here is the output from Dismo:

*Regularized training gain is 3.987, training AUC is 0.997, unregularized
training gain is 4.704.
Algorithm terminated after 500 iterations (6 seconds).

The follow settings were used during the run:
28 presence records used for training.
10000 points used to determine the Maxent distribution (background points).
Environmental layers used (all continuous): bio1 bio10 bio11 bio12 bio13
bio14 bio15 bio16 bio17 bio18 bio19 bio2 bio3 bio4 bio5 bio6 bio7 bio8 bio9
Regularization values: linear/quadratic/product: 0.288, categorical: 0.250,
threshold: 1.720, hinge: 0.500
Feature types used: linear quadratic hinge
outputformat: raw
outputdirectory:
/var/folders/4t/f1r24pf90d724kpr9m7bpl640000gp/T/R_raster_tmp/Pascal/maxent/9339181644
samplesfile:
/var/folders/4t/f1r24pf90d724kpr9m7bpl640000gp/T/R_raster_tmp/Pascal/maxent/9339181644/presence
environmentallayers:
/var/folders/4t/f1r24pf90d724kpr9m7bpl640000gp/T/R_raster_tmp/Pascal/maxent/9339181644/absence
removeduplicates: false
addsamplestobackground: false
autorun: true
visible: false
Command line used: autorun -e
/var/folders/4t/f1r24pf90d724kpr9m7bpl640000gp/T/R_raster_tmp/Pascal/maxent/9339181644/absence
-o
/var/folders/4t/f1r24pf90d724kpr9m7bpl640000gp/T/R_raster_tmp/Pascal/maxent/9339181644
-s
/var/folders/4t/f1r24pf90d724kpr9m7bpl640000gp/T/R_raster_tmp/Pascal/maxent/9339181644/presence
-z outputformat=raw removeduplicates=false addsamplestobackground=false
betamultiplier=1.0

Command line to repeat this species model: java density.MaxEnt nowarnings
noprefixes -E "" -E species outputformat=raw
outputdirectory=/var/folders/4t/f1r24pf90d724kpr9m7bpl640000gp/T/R_raster_tmp/Pascal/maxent/9339181644
samplesfile=/var/folders/4t/f1r24pf90d724kpr9m7bpl640000gp/T/R_raster_tmp/Pascal/maxent/9339181644/presence
environmentallayers=/var/folders/4t/f1r24pf90d724kpr9m7bpl640000gp/T/R_raster_tmp/Pascal/maxent/9339181644/absence
noremoveduplicates noaddsamplestobackground autorun novisible*

-- 
Pascal Title, MSc.
PhD student, Rabosky Lab <http://cteg.berkeley.edu/~rabosky/Home.html>
Dept of Ecology and Evolutionary Biology
University of Michigan
ptitle@umich.edu

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