Simulate_demography {SharkDemography}

Monte Carlo simulations of Leslie matrix models

Description

This is a wrapper function for 'Calculate_demography' which runs this function the specified number of times.

Usage

Simulate_demography(
  n,
  data,
  AALC = NULL,
  AAFC = NULL,
  F. = 0,
  M.estimators = NULL,
  Verbatim = TRUE
)

Arguments

n

The number of specified Monte Carlo simulations to run

data

A multi-level list of the class 'Demography.inputs' produced from the 'create_data_input' function and then manually completed.

AALC

Age-at-last-capture which can be specified by the user. Must be an integer age which can include zero.

AAFC

Age-at-first-capture which can be specified by the user.Must be an integer age which can include zero to indicate the availability of the population to capture from birth.

F.

The instantaneous rate of fishing mortality 'F'. This will be applied to all ages available to capture as defined by either the AALC or AAFC arguments.

M.estimators

Any specific natural mortality estimators to be included in the analysis. Only one will be used in each run which is randomly selected. Must be a single estimator or a vector of estimators. These can include: "Pet.Wro","Jensen.mat","Chen.Yuan", "Then_hoenig","Then_pauly", "Jensen.mat","Charnov" or "Chen.Want". If none are specified then all applicable estimators could be chosen.

Verbatim

Print summary results to screen if TRUE. When FALSE, the progress bar is also disabled.

Value

A list with two data.frames. The first is the summary of the Monte Carlo simulations for all parameters calculated by the 'Calculate_demography' function with mean and 95% quantiles. The second is all of the results for each parameter from individual simulations so that their distributions can be interrogated further.

Examples

# load Silky shark data produced by create_data_input()
# Type `?create_data_input()` for details
data("Silky_data")

# Run function to get conduct Monte Carlo Simulations using
# `Calculate_demography()`  for all available natural mortality estimators.
# Set n = at least 1000 for full analysis but use n = 100 for testing

Simulate_demography(n = 100, Silky_data)