validate_pa_fit_time

This function validates whether the time periods of the presence/absence data match the environmental layers.

internal

A user-friendly 'shiny' application for Bayesian machine
learning analysis of marine species distributions. GLOSSA (Global
Species Spatiotemporal Analysis) uses Bayesian Additive Regression
Trees (BART; Chipman, George, and McCulloch (2010)
<doi:10.1214/09-AOAS285>) to model species distributions with
intuitive workflows for data upload, processing, model fitting, and
result visualization. It supports presence-absence and presence-only
data (with pseudo-absence generation), spatial thinning,
cross-validation, and scenario-based projections. GLOSSA is designed
to facilitate ecological research by providing easy-to-use tools for
analyzing and visualizing marine species distributions across
different spatial and temporal scales.

Jorge Mestre-Tomás

glossa

User-Friendly 'shiny' App for Bayesian Species Distribution
Models

Alba Fuster-Alonso

validate_pa_fit_time function

<dl><dt>pa_data</dt>
<dd>Data frame containing the presence/absence data with a 'timestamp' column.</dd>
<dt>fit_layers_path</dt>
<dd>Path to the ZIP file containing fit layers.</dd>
<dt>show_modal</dt>
<dd>Optional. Logical. Whether to show a modal notification for warnings. Default is FALSE.</dd></dl>

Arguments

Validate Match Between Presence/Absence Files and Fit Layers — validate_pa_fit_time

<dl>

<dt>pa_data</dt>
<dd>Data frame containing the presence/absence data with a 'timestamp' column.</dd>


<dt>fit_layers_path</dt>
<dd>Path to the ZIP file containing fit layers.</dd>


<dt>show_modal</dt>
<dd>Optional. Logical. Whether to show a modal notification for warnings. Default is FALSE.</dd>

</dl>

validate_pa_fit_time: Validate Match Between Presence/Absence Files and Fit Layers

Description

Usage

Value

Arguments