SimSurvey0.1.6 package

Test Surveys by Simulating Spatially-Correlated Populations

convert_N

Convert abundance-at-age matrix to abundance-at-length

dot-Q

Helper function to generate precision matrix Q for simulation

error_stats

Calculate common error statistics

expand_surveys

Set-up a series of surveys from all combinations of settings supplied

fibonacci

Generate Fibonacci sequence

group_lengths

Convert length to length group

icc

Calculate intraclass correlation

make_grid

Make a depth stratified survey grid

make_mesh

Make an R-INLA mesh based off a grid

object_size

Print object size

plot_trend

Simple plotting functions

reexports

Objects exported from other packages

round_sim

Round simulated population

run_strat

Run stratified analysis on simulated data

sim_abundance

Simulate basic population dynamics model

sim_ays_covar

Simulate age-year-space covariance

sim_ays_covar_spde

Simulate age-year-space covariance using SPDE approach

sim_distribution

Simulate spatial and temporal distribution

sim_logistic

Closure for simulating logistic curve

sim_nlf

Define a non-linear relationship

sim_parabola

Define a parabolic relationship

sim_R

Simulate starting abundance, random recruitment and total mortality

sim_sets

Simulate survey sets

sim_survey

Simulate stratified-random survey

sim_survey_parallel

Simulate stratified random surveys using parallel computation

sim_vonB

Closure for simulating length given age using von Bertalanffy notation

strat_data

Prepare simulated data for stratified analysis

strat_error

Calculate error of stratified estimates

strat_means

Calculate stratified means, variances and confidence intervals across ...

survey_lite_mesh

Lite sample survey mesh and related items

test_surveys

Test sampling design of multiple surveys using a stratified analysis

vis_sim

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).

  • Maintainer: Paul Regular
  • License: GPL-3
  • Last published: 2023-09-19