Print_Default_ModelingOptions: Get default values of BIOMOD inner models' options

In biomod2: Ensemble Platform for Species Distribution Modeling

Description

This function print the default parameters used to build each model.

Usage

Print_Default_ModelingOptions()

Details

This function is useful to parameterize the selected models. It gives a formated list of all parameters the user can modify. You can copy this function output, modify all parameters you want in a text editor and paste the modified string as argument to (BIOMOD_ModelingOptions) function.

Value

Nothing returned.

Author(s)

Wilfried Thuiller, Damien Georges

Examples

# print default models options
Print_Default_ModelingOptions()

Example output

Loading required package: sp
Loading required package: raster
Loading required package: parallel
Loading required package: reshape
Loading required package: ggplot2
biomod2 3.3-7 loaded.

Type browseVignettes(package='biomod2') to access directly biomod2 vignettes.

 Defaut modeling options. copy, change what you want paste it as arg to BIOMOD_ModelingOptions


-=-=-=-=-=-=-=-=-=-=-=-=-=-=  'BIOMOD.Model.Options'  -=-=-=-=-=-=-=-=-=-=-=-=-=-=


GLM = list( type = 'quadratic',
            interaction.level = 0,
            myFormula = NULL,
            test = 'AIC',
            family = binomial(link = 'logit'),
            mustart = 0.5,
            control = glm.control(epsilon = 1e-08, maxit = 50, trace = FALSE
) ),


GBM = list( distribution = 'bernoulli',
            n.trees = 2500,
            interaction.depth = 7,
            n.minobsinnode = 5,
            shrinkage = 0.001,
            bag.fraction = 0.5,
            train.fraction = 1,
            cv.folds = 3,
            keep.data = FALSE,
            verbose = FALSE,
            perf.method = 'cv'),

GAM = list( algo = 'GAM_mgcv',
            type = 's_smoother',
            k = -1,
            interaction.level = 0,
            myFormula = NULL,
            family = binomial(link = 'logit'),
            method = 'GCV.Cp',
            optimizer = c('outer','newton'),
            select = FALSE,
            knots = NULL,
            paraPen = NULL,
            control = list(nthreads = 1, irls.reg = 0, epsilon = 1e-07
, maxit = 200, trace = FALSE, mgcv.tol = 1e-07, mgcv.half = 15
, rank.tol = 1.49011611938477e-08
, nlm = list(ndigit=7, gradtol=1e-06, stepmax=2, steptol=1e-04, iterlim=200, check.analyticals=0)
, optim = list(factr=1e+07)
, newton = list(conv.tol=1e-06, maxNstep=5, maxSstep=2, maxHalf=30, use.svd=0)
, outerPIsteps = 0, idLinksBases = TRUE, scalePenalty = TRUE, keepData = FALSE
, scale.est = fletcher, edge.correct = FALSE) ),


CTA = list( method = 'class',
            parms = 'default',
            cost = NULL,
            control = list(xval = 5, minbucket = 5, minsplit = 5, cp = 0.001
, maxdepth = 25) ),


ANN = list( NbCV = 5,
            size = NULL,
            decay = NULL,
            rang = 0.1,
            maxit = 200),

SRE = list( quant = 0.025),

FDA = list( method = 'mars',
            add_args = NULL),

MARS = list( type = 'simple',
             interaction.level = 0,
             myFormula = NULL,
             nk = NULL,
             penalty = 2,
             thresh = 0.001,
             nprune = NULL,
             pmethod = 'backward'),

RF = list( do.classif = TRUE,
           ntree = 500,
           mtry = 'default',
           nodesize = 5,
           maxnodes = NULL),

MAXENT.Phillips = list( path_to_maxent.jar = '/work/tmp',
               memory_allocated = 512,
               background_data_dir = 'default',
               maximumbackground = 'default',
               maximumiterations = 200,
               visible = FALSE,
               linear = TRUE,
               quadratic = TRUE,
               product = TRUE,
               threshold = TRUE,
               hinge = TRUE,
               lq2lqptthreshold = 80,
               l2lqthreshold = 10,
               hingethreshold = 15,
               beta_threshold = -1,
               beta_categorical = -1,
               beta_lqp = -1,
               beta_hinge = -1,
               betamultiplier = 1,
               defaultprevalence = 0.5),

MAXENT.Tsuruoka = list( l1_regularizer = 0,
                        l2_regularizer = 0,
                        use_sgd = FALSE,
                        set_heldout = 0,
                        verbose = FALSE)
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biomod2 documentation built on May 2, 2019, 5:08 p.m.