Test Surveys by Simulating Spatially-Correlated Populations
Convert abundance-at-age matrix to abundance-at-length
Helper function to generate precision matrix Q for simulation
Calculate common error statistics
Set-up a series of surveys from all combinations of settings supplied
Generate Fibonacci sequence
Convert length to length group
Calculate intraclass correlation
Make a depth stratified survey grid
Make an R-INLA mesh based off a grid
Print object size
Simple plotting functions
Objects exported from other packages
Round simulated population
Run stratified analysis on simulated data
Simulate basic population dynamics model
Simulate age-year-space covariance
Simulate age-year-space covariance using SPDE approach
Simulate spatial and temporal distribution
Closure for simulating logistic curve
Define a non-linear relationship
Define a parabolic relationship
Simulate starting abundance, random recruitment and total mortality
Simulate survey sets
Simulate stratified-random survey
Simulate stratified random surveys using parallel computation
Closure for simulating length given age using von Bertalanffy notation
Prepare simulated data for stratified analysis
Calculate error of stratified estimates
Calculate stratified means, variances and confidence intervals across ...
Lite sample survey mesh and related items
Test sampling design of multiple surveys using a stratified analysis
Make a flexdashboard for visualizing the simulation
Simulate age-structured populations that vary in space and time and explore the efficacy of a range of built-in or user-defined sampling protocols to reproduce the population parameters of the known population. (See Regular et al. (2020) <doi:10.1371/journal.pone.0232822> for more details).
Useful links