borealis_simulated

Simulated biomass data for test and practice.

datasets

Implement a GAM-based (Generalized Additive Models) spatial surplus
production model (spatial SPM), aimed at modeling northern shrimp population
in Atlantic Canada but potentially to any stock in any location. The package
is opinionated in its implementation of SPMs as it internally makes the choice
to use penalized spatial gams with time lags. However, it also aims to provide
options for the user to customize their model. The methods are described in
Pedersen et al. (2022, <https://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs-DocRech/2022/2022_062-eng.html>).

Valentin Lucet

sspm

Spatial Surplus Production Model Framework for Northern Shrimp
Populations

Eric Pedersen

borealis_simulated function

A data frame:<dl>
<dt>year_f</dt>
<dd>Year as a factor</dd><dt>sfa</dt>
<dd>SFA ID number</dd><dt>weight_per_km2</dt>
<dd>Simualated biomass in kg per km2</dd><dt>temp_at_bottom</dt>
<dd>Simulated water temperature</dd><dt>lon_dec</dt>
<dd>Longitude</dd><dt>lat_dec</dt>
<dd>Latitude</dd><dt>row</dt>
<dd>Row ID</dd><dt>uniqueID</dt>
<dd>Unique ID for simulated observation</dd>
</dl>

Format

Simulated biomass data — borealis_simulated

A data frame:<dl>
<dt>year_f</dt>
<dd>Year as a factor</dd>

<dt>sfa</dt>
<dd>SFA ID number</dd>

<dt>weight_per_km2</dt>
<dd>Simualated biomass in kg per km2</dd>

<dt>temp_at_bottom</dt>
<dd>Simulated water temperature</dd>

<dt>lon_dec</dt>
<dd>Longitude</dd>

<dt>lat_dec</dt>
<dd>Latitude</dd>

<dt>row</dt>
<dd>Row ID</dd>

<dt>uniqueID</dt>
<dd>Unique ID for simulated observation</dd>


</dl>

borealis_simulated: Simulated biomass data

Description

Usage

Arguments

Format