```{asis, echo = {{model_maxent_knit}}, eval = {{model_maxent_knit & !cat_envs_knit}}, include = {{model_maxent_knit & !cat_envs_knit}}}

Build and Evaluate Niche Model

Generating a species distribution model using the r '{{algMaxent_rmd}}' algorithm as implemented in ENMeval V2.0 (with clamping = r {{clampSel_rmd}}). For tuning using r {{fcs_rmd}} feature classes and regularization multipliers in the r {{rms_rmd}} range increasing by r {{rmsStep_rmd}}. Not using any categorical predictor variables.

```r}, include = {{model_maxent_knit & !cat_envs_knit}}}
# Run maxent model for the selected species
model_{{spAbr}} <- model_maxent(
  occs = occs_{{spAbr}},
  bg = bgEnvsVals_{{spAbr}},
  user.grp = groups_{{spAbr}}, 
  bgMsk = bgMask_{{spAbr}},
  rms = {{rms_rmd}}, 
  rmsStep = {{rmsStep_rmd}},
  fcs = {{fcs_rmd}},
  clampSel = {{clampSel_rmd}},
  algMaxent = "{{algMaxent_rmd}}",
  parallel = {{parallel_rmd}},
  numCores = {{numCores_rmd}})

```{asis, echo = {{model_maxent_knit & cat_envs_knit}}, eval = {{model_maxent_knit & cat_envs_knit}}, include = {{model_maxent_knit & cat_envs_knit}}}

Build and Evaluate Niche Model

Generating a species distribution model using the r '{{algMaxent_rmd}}' algorithm as implemented in ENMeval V2.0 (with clamping = r {{clampSel_rmd}}). For tuning using r {{fcs_rmd}} feature classes and regularization multipliers in the r {{rms_rmd}} range increasing by r {{rmsStep_rmd}}. Using a total of r {{catEnvsNum_rmd}} categorical predictor variables.

```r}, include = {{model_maxent_knit & cat_envs_knit}}}
# Run maxent model for the selected species
model_{{spAbr}} <- model_maxent(
  occs = occs_{{spAbr}},
  bg = bgEnvsVals_{{spAbr}},
  user.grp = groups_{{spAbr}}, 
  bgMsk = bgMask_{{spAbr}},
  rms = {{rms_rmd}}, 
  rmsStep = {{rmsStep_rmd}},
  fcs = {{fcs_rmd}},
  clampSel = {{clampSel_rmd}},
  algMaxent = "{{algMaxent_rmd}}",
  catEnvs = "{{catEnvs_rmd}}",
  parallel = {{parallel_rmd}},
  numCores = {{numCores_rmd}})


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wallace documentation built on May 29, 2024, 1:16 a.m.