tmr_glm

<p>Output from <code>build_temporal_glm</code> fit to <code>tmr_partition</code>
and <code>tmr_absences</code> with the formula
<code>~ forest_cover + prseas + elevation</code>, a logit link, and TSS-based
threshold selection. One model per fold. Loaded with
<code>data(tmr_glm)</code>.</p>

datasets

Increases the ease of implementing a temporally-explicit modeling
methodology when building ecological niche and species distribution models.
Provides functions to assist with three major steps of temporally-explicit
models: (i) preprocessing species and environmental data and generating
suitable background or pseudoabsence data, (ii) building a niche model and
generating temporally-explicit predictions from that model, and (iii) model
postprocessing to explore spatiotemporal trends in model predictions.
Methodological and theoretical foundations are described in Ingenloff and
Peterson (2021) <doi:10.1111/2041-210X.13564>, Franklin (2010, ISBN:9780521700023),
Peterson et al. (2011, ISBN:9780691136882), Blonder (2018) <doi:10.1111/ecog.03187>,
Senay et al. (2013) <doi:10.1371/journal.pone.0071218>, and Li and Zhang (2024) <doi:10.48550/arXiv.2404.05933>.

Connor Hughes

TemporalModelR

Temporally Explicit Species Distribution Modelling

Mariana Castaneda-Guzman

Luis E. Escobar

tmr_glm function

<p>A list of class <code>"TemporalGLM"</code> as returned by
  <code>build_temporal_glm</code>, containing <code>$models</code>,
  <code>$thresholds</code>, <code>$threshold_method</code>, <code>$model_formula</code>,
  <code>$link</code>, <code>$model_vars</code>, <code>$fold_training_data</code>,
  <code>$fold_test_metrics</code>, <code>$output_dir</code>, <code>$model_type</code>,
  and <code>$plots</code>.</p>

tmr_glm: Pre-built GLM result (seasonal workflow)

Description

Usage

Arguments

Format