man-roxygen/Obs_template.R

In Blue-Matter/MSEtool: Management Strategy Evaluation Toolkit

# This file is auto-generated by build_tools/write_class_definitions.R
# Do not edit by hand


#' @slot Name The name of the Observation error object. Single value. Character
#'  string.
#' @slot Cobs Observation error around the total catch. Observation error in
#'  the total catch is expressed as a coefficient of variation (CV). Cobs requires
#'  upper and lower bounds of a uniform distribution, and for each simulation a CV
#'  is sampled from this distribution. Each CV is used to specify a log-normal
#'  error distribution with a mean of 1 and a standard deviation equal to the
#'  sampled CV. The yearly observation error values for the catch data are then
#'  drawn from this distribution. For each time step the simulation model records
#'  the true catch, but the observed catch is generated by applying this yearly
#'  error term (plus any bias, if specified) to the true catch.
#' @slot Cbiascv Log-normally distributed coefficient of variation controlling
#'  the sampling bias in observed catch for each simulation. Bias occurs when
#'  catches are systematically skewed away from the true catch level (for example,
#'  due to underreporting of catch or undetected illegal catches). Cbiascv is a
#'  single value specifying the standard deviation of a log-normal distribution
#'  with a mean of 1 and a standard deviation equal to the sampled CV. For each
#'  simulation a bias value is drawn from this distribution, and that bias is
#'  applied across all years.
#' @slot CAA_nsamp Number of catch-at-age observations collected per time step.
#'  For each time step a single value is drawn from a uniform distribution
#'  specified by the upper and lower bounds provided. Positive integers.
#' @slot CAA_ESS Effective sample size of catch-at-age observations collected
#'  per time step. For each time step a single value is drawn from a uniform
#'  distribution specified by the upper and lower bounds provided. CAA_ESS should
#'  not exceed CAA_nsamp. If greater than 1, then this is the multinomial
#'  distribution sample size. If less than 1, this is the coefficient of variation
#'  for the logistic normal distribution (see help doucmentation for simCAA for
#'  details).
#' @slot CAL_nsamp Number of catch-at-length observations collected per time
#'  step. For each time step a single value is drawn from a uniform distribution
#'  specified by the upper and lower bounds provided. Positive integers.
#' @slot CAL_ESS Effective sample size. For each time step a single value is
#'  drawn from a uniform distribution specified by the upper and lower bounds
#'  provided. CAL_ESS should not exceed CAL_nsamp. Positive integers.
#' @slot Iobs Observation error in the relative abundance index expressed as a
#'  coefficient of variation (CV). Iobs requires upper and lower bounds of a
#'  uniform distribution, and for each simulation a CV is sampled from this
#'  distribution. Each CV is used to specify a log-normal error distribution with a
#'  mean of 1 and a standard deviation equal to the sampled CV. The yearly
#'  observation error values for the index of abundance data are then drawn from
#'  this distribution. For each time step the simulation model records the true
#'  change in abundance, but the observed index is generated by applying this
#'  yearly error term (plus any bias, if specified) to the true relative change in
#'  abundance. Positive real numbers.
#' @slot Btobs Observation error in the absolute abundance expressed as a
#'  coefficient of variation (CV). Btobs requires upper and lower bounds of a
#'  uniform distribution, and for each simulation a CV is sampled from this
#'  distribution. Each CV is used to specify a log-normal error distribution with a
#'  mean of 1 and a standard deviation equal to the sampled CV. The yearly
#'  observation error values for the absolute abundance data are then drawn from
#'  this distribution. For each time step the simulation model records the true
#'  abundance, but the observed abundance is generated by applying this yearly
#'  error term (plus any bias, if specified) to the true abundance. Positive real
#'  numbers.
#' @slot Btbiascv Log-normally distributed coefficient (CV) controlling error
#'  in observations of the current stock biomass. Bias occurs when the observed
#'  index of abundance is is systematically higher or lower than the true relative
#'  abundance. Btbiascv is a single value specifying the standard deviation of a
#'  log-normal distribution with a mean of 1 and a standard deviation equal to the
#'  sampled CV. For each simulation a bias value is drawn from this distribution,
#'  and that bias is applied across all years. Positive real numbers.
#' @slot beta A parameter controlling hyperstability/hyperdepletion in the
#'  measurement of abundance. For each simulation a single value is drawn from a
#'  uniform distribution specified by the upper and lower bounds provided. Values
#'  below 1 lead to hyperstability (the observed index decreases more slowly than
#'  the true abundance) and values above 1 lead to hyperdepletion (the observed
#'  index decreases more rapidly than true abundance).  Positive real numbers.
#' @slot LenMbiascv Log-normal coefficient of variation for sampling bias in
#'  observed length at 50 percent maturity. LenMbiascv is a single value specifying
#'  the standard deviation of a log-normal distribution with a mean of 1 and a
#'  standard deviation equal to the sampled CV. For each simulation a bias value is
#'  drawn from this distribution, and that bias is applied across all years.
#'  Positive real numbers.
#' @slot Mbiascv Log-normal coefficient of variation for sampling bias in
#'  observed natural mortality rate. 
#'  Mbiascv is a single value specifying the standard deviation of a log-normal
#'  distribution with a mean of 1 and a standard deviation equal to the sampled CV.
#'  For each simulation a bias value is drawn from this distribution, and that bias
#'  is applied across all years. Positive real numbers.
#' @slot Kbiascv Log-normal coefficient of variation for sampling bias in
#'  observed growth parameter K. Kbiascv is a single value specifying the standard
#'  deviation of a log-normal distribution with a mean of 1 and a standard
#'  deviation equal to the sampled CV. For each simulation a bias value is drawn
#'  from this distribution, and that bias is applied across all years. Positive
#'  real numbers.
#' @slot t0biascv Log-normal coefficient of variation for sampling bias in
#'  observed t0. t0biascv is a single value specifying the standard deviation of a
#'  log-normal distribution with a mean of 1 and a standard deviation equal to the
#'  sampled CV. For each simulation a bias value is drawn from this distribution,
#'  and that bias is applied across all years. Positive real numbers.
#' @slot Linfbiascv Log-normal coefficient of variation for sampling bias in
#'  observed maximum length. Linfbiascv is a single value specifying the standard
#'  deviation of a log-normal distribution with a mean of 1 and a standard
#'  deviation equal to the sampled CV. For each simulation a bias value is drawn
#'  from this distribution, and that bias is applied across all years. Positive
#'  real numbers.
#' @slot LFCbiascv Log-normal coefficient of variation for sampling bias in
#'  observed length at first capture. LFCbiascv is a single value specifying the
#'  standard deviation of a log-normal distribution with a mean of 1 and a standard
#'  deviation equal to the sampled CV. For each simulation a bias value is drawn
#'  from this distribution, and that bias is applied across all years. Positive
#'  real numbers.
#' @slot LFSbiascv Log-normal coefficient of variation for sampling bias in
#'  length-at-full selection. LFSbiascv is a single value specifying the standard
#'  deviation of a log-normal distribution with a mean of 1 and a standard
#'  deviation equal to the sampled CV. For each simulation a bias value is drawn
#'  from this distribution, and that bias is applied across all years. Positive
#'  real numbers.
#' @slot FMSY_Mbiascv Log-normal coefficient of variation for sampling bias in
#'  estimates of the ratio of the fishing mortality rate that gives the maximum
#'  sustainable yield relative to the assumed instantaneous natural mortality rate.
#'  FMSY/M. FMSY_Mbiascv is a single value specifying the standard deviation of a
#'  log-normal distribution with a mean of 1 and a standard deviation equal to the
#'  sampled CV. For each simulation a bias value is drawn from this distribution,
#'  and that bias is applied across all years. Positive real numbers.
#' @slot BMSY_B0biascv Log-normal coefficient of variation for sampling bias in
#'  estimates of the BMSY relative to unfished biomass (BMSY/B0). BMSY_B0biascv is
#'  a single value specifying the standard deviation of a log-normal distribution
#'  with a mean of 1 and a standard deviation equal to the sampled CV. For each
#'  simulation a bias value is drawn from this distribution, and that bias is
#'  applied across all years. Positive real numbers.
#' @slot Irefbiascv Log-normal coefficient of variation for sampling bias in
#'  the observed relative index of abundance (Iref). Irefbiascv is a single value
#'  specifying the standard deviation of a log-normal distribution with a mean of 1
#'  and a standard deviation equal to the sampled CV. For each simulation a bias
#'  value is drawn from this distribution, and that bias is applied across all
#'  years. Positive real numbers.
#' @slot Brefbiascv Log-normal coefficient of variation for sampling bias in
#'  the observed reference biomass (Bref). Brefbiascv is a single value specifying
#'  the standard deviation of a log-normal distribution with a mean of 1 and a
#'  standard deviation equal to the sampled CV. For each simulation a bias value is
#'  drawn from this distribution, and that bias is applied across all years.
#'  Positive real numbers.
#' @slot Crefbiascv Log-normal coefficient of variation for sampling bias in
#'  the observed reference catch (Cref). Crefbiascv is a single value specifying
#'  the standard deviation of a log-normal distribution with a mean of 1 and a
#'  standard deviation equal to the sampled CV. For each simulation a bias value is
#'  drawn from this distribution, and that bias is applied across all years.
#'  Positive real numbers.
#' @slot Dbiascv Log-normal coefficient of variation for sampling bias in the
#'  observed depletion level.  Dbiascv is a single value specifying the standard
#'  deviation of a log-normal distribution with a mean of 1 and a standard
#'  deviation equal to the sampled CV. For each simulation a bias value is drawn
#'  from this distribution, and that bias is applied across all years. Positive
#'  real numbers.
#' @slot Dobs Log-normal coefficient of variation controlling error in
#'  observations of stock depletion among years. Observation error in the depletion
#'  expressed as a coefficient of variation (CV). Dobs requires the upper and lower
#'  bounds of a uniform distribution, and for each simulation a CV is sampled from
#'  this distribution. Each CV is used to specify a log-normal error distribution
#'  with a mean of 1 and a standard deviation equal to the sampled CV. The yearly
#'  observation error values for the depletion data are then drawn from this
#'  distribution. For each time step the simulation model records the true
#'  depletion, but the observed depletion is generated by applying this yearly
#'  error term (plus any bias, if specified) to the true depletion.
#' @slot hbiascv Log-normal coefficient of variation for sampling persistent
#'  bias in steepness. hbiascv is a single value specifying the standard deviation
#'  of a log-normal distribution with a mean of 1 and a standard deviation equal to
#'  the sampled CV. For each simulation a bias value is drawn from this
#'  distribution, and that bias is applied across all years. Positive real numbers.
#' @slot Recbiascv Log-normal coefficient of variation for sampling persistent
#'  bias in recent recruitment strength. Recbiascv requires the upper and lower
#'  bounds of a uniform distribution, and for each simulation a CV is sampled from
#'  this distribution. Each CV is used to specify a log-normal error distribution
#'  with a mean of 1 and a standard deviation equal to the sampled CV. The yearly
#'  bias values for the depletion data are then drawn from this distribution.
#'  Positive real numbers.
#' @slot sigmaRbiascv Log-normal coefficient of variation for sampling
#'  persistent bias in recruitment variability. sigmaRbiascv is a single value
#'  specifying the standard deviation of a log-normal distribution with a mean of 1
#'  and a standard deviation equal to the sampled CV. For each simulation a bias
#'  value is drawn from this distribution, and that bias is applied across all
#'  years. Positive real numbers.
#' @slot Eobs Observation error around the total effort. Observation error in
#'  the total effort is expressed as a coefficient of variation (CV). Eobs requires
#'  upper and lower bounds of a uniform distribution, and for each simulation a CV
#'  is sampled from this distribution. Each CV is used to specify a log-normal
#'  error distribution with a mean of 1 and a standard deviation equal to the
#'  sampled CV. The yearly observation error values for the effort data are then
#'  drawn from this distribution. For each time step the simulation model records
#'  the true effort, but the observed effort is generated by applying this yearly
#'  error term (plus any bias, if specified) to the true effort.
#' @slot Ebiascv Log-normally distributed coefficient of variation controlling
#'  the sampling bias in observed effort for each simulation. Bias occurs when
#'  effort is systematically skewed away from the true effort level. Ebiascv is a
#'  single value specifying the standard deviation of a log-normal distribution
#'  with a mean of 1 and a standard deviation equal to the sampled CV. For each
#'  simulation a bias value is drawn from this distribution, and that bias is
#'  applied across all years.