calcCohortProgression: Calculate the cohort progression

In wStockhausen/shinyTC.CohortProgression: Package to simulate a Tanner crab cohort progression using Shiny

Description

Function to calculate the cohort progressionn.

Usage

calcCohortProgression(configInfo, nmInfo, mltInfo, grwInfo, m2mInfo,
  recInfo, input, verbose = FALSE)

Arguments

configInfo	- list created by setConfigInfo with model configuration elements
nmInfo	- list created by natmortServer with model natural mortality rates elements
mltInfo	- list created by moltServer with model molt probability elements
grwInfo	- list created by growthServer with growth transition elements
m2mInfo	- list created by m2mServer with prM2M elements
recInfo	- list created by recServer with recruitment distribution elements
input	- list with cohort progression parameters and other information
verbose	- flag (T/F) to print debugging info

Details

Returns a list with elements:<cr> <ul> <li> params - a list with input parameter values </li> <li> n_ymsz - an array with the cohort progression </li> <li> mdfrN_ymsz - a dataframe wtih the cohort progression </li> <li> p_ymsz - an array with the normalized cohort progression </li> <li> mdfrP_ymsz - a dataframe wtih the normalized cohort progression </li> <li> n_msz - an array with the equilibrium size distribution </li> <li> mdfrN_msz - a dataframe wtih the equilibrium size distribution </li> <li> p_msz - an array with the normalized equilibrium size distribution </li> <li> mdfrP_msz - a dataframe wtih the normalized equilibrium size distribution </li> </ul>

The input list must have the following elements:<cr> <ul> <li> maxAge - max age (years) to include in progression </li> </ul>

Value

list - list with n_msz as a vector and as a dataframe (see @details )

wStockhausen/shinyTC.CohortProgression documentation built on July 19, 2021, 5:32 a.m.