R/Conditioning_create.indices.data.R
In flr/FLBEIA: Bio-Economic Impact Assessment of Management Strategies using FLR
Defines functions
create.indices.data
Documented in
create.indices.data
###############################################################################
# AUTHOR(DATE): Agurtzane Urtizberea, Dorleta Garcia and Sonia Sanchez
# RESEARCH INSTITUTE: AZTI-TECNALIA
# TITLE: create.indices.data
# NOTE #1: Return a list with FLIndex objects
###############################################################################
#-------------------------------------------------------------------------
#'
#' FLBEIA easy conditioning: indices argument creator
#'
#' create.indices.data function creates an FLIndices object
#'
#' @param ni Number of iterations (number).
#' @param ns Number of seasons (number).
#' @param yrs A vector with c(first.yr,proj.yr, last.yr) where
#'\itemize{
#' \item first.yr: First year of simulation (number).
#' \item proj.yr: First year of projection (number).
#' \item last.yr: Last year of projection (number).}
#' @param stks.data A list with the names of the stocks with indices and the following elements:
#'\itemize{
#' \item stk.unit: Number of units of the stock (number).
#' \item stk.age.min: Minimum age class of the stock (number).
#' \item stk.age.max: Maximum age class of the stock (number).
#' \item stk_indices: Name of indices for the stock 'stk' (vector).
#' \item stk_ind_index.flq: Historical index data for index 'ind' of stock 'stk' (FLQuant).}
#' Optionals:
#'\itemize{
#' \item stk_ind_type: Type of index (character).
#' \item stk_ind_distribution: Name of the statistical distribution of the 'ind' index values for stock 'stk' (character).
#' \item stk_ind_index.var.flq: Variability in 'ind' index of stock 'stk' (FLQuant).
#' \item stk_ind_index.q.flq: Catchability for 'ind' index of stock 'stk' (FLQuant).
#' \item stk_ind_catch.n.flq: Catch at age in numbers for 'ind' index of stock 'stk'(FLQuant).
#' \item stk_ind_catch.wt.flq: Mean weight at age in the catch for 'ind' index of stock 'stk' (FLQuant).
#' \item stk_ind_effort.flq: Effort for 'ind' index of stock 'stk' (FLQuant).
#' \item stk_ind_sel.pattern.flq: Selection pattern for 'ind' index of stock 'stk' (FLQuant).
#' \item stk_ind_range.min: Minimum age in 'ind' index of stock 'stk' (number).
#' \item stk_ind_range.max: Maximum age in 'ind' index of stock 'stk' (number).
#' \item stk_ind_range.plusgroup: Plusgroup age in 'ind' index of stock 'stk' (number).
#' \item stk_ind_range.minyear: First year with 'ind' index data of stock 'stk' (number).
#' \item stk_ind_range.maxyear: Last year with 'ind' index data of stock 'stk' (number).
#' \item stk_ind_range.startf: Minimum age for calculating average fishing mortality for 'ind' index of stock 'stk' (number).
#' \item stk_ind_range.endf: Maximum age for calculating average fishing mortality for 'ind' index of stock 'stk' (number).}
#'
#' @return An FLIndices object.
#'
#
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
# Section 1: Is there any index data?
# Section 2: Create indices
# 2.1 Historical data per stock
# 2.2 Check dimensions
#-------------------------------------------------------------------------------
create.indices.data <- function(yrs,ns,ni,stks.data){
#==============================================================================
# Section 1: Is there any index data?
#==============================================================================
ind <- unlist(sapply(stks.data,function(x) grep(x, pattern="_indices",value=TRUE)))
nms.stks.index <- unique(sub('.*?^(.*?)_indices*', '\\1', ind))
indices <- NULL
if(length(nms.stks.index)==0){
cat("Warning:indices is NULL \n")
}else{
#==============================================================================
# Section 2: indices
#==============================================================================
n.stks.index <- length(nms.stks.index)
indices <- vector('list',n.stks.index)
names(indices) <- nms.stks.index
first.yr <- yrs[["first.yr"]]
proj.yr <- yrs[["proj.yr"]]
last.yr <- yrs[["last.yr"]]
proj.yrs <- as.character(proj.yr:last.yr)
hist.yrs <- as.character(first.yr:(proj.yr-1))
ny <- length(first.yr:last.yr)
list.stks.unit <- lapply(stks.data, function(ch) grep(pattern="unit", ch, value = TRUE))
list.stks.age <- lapply(stks.data, function(ch) grep(pattern="age", ch, value = TRUE))
list.stks.flqa <- create.list.stks.flqa(nms.stks.index,yrs,ni,ns,list.stks.unit,list.stks.age)
list.stks.flq <- create.list.stks.flq(nms.stks.index,yrs,ni,ns,list.stks.unit)
#-----------------------------------------------------------------------------
# Section 2.1: Historical data per stock
#-----------------------------------------------------------------------------
for (i in 1:n.stks.index){
stk <- nms.stks.index[i]
cat('=============', stk,'index','=============\n')
nms.stk.index <- get(grep(stks.data[[stk]],pattern="_indices", value = TRUE))
list.stk.index <- list()
for(j in 1:length(nms.stk.index)){
nm.stk.index <- nms.stk.index[j]
flqa <- list.stks.flqa[[stk]]
flq <- list.stks.flq[[stk]]
stk.index <- get(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_index.flq',sep=''), value = TRUE))
stk.index.type <- get(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_type',sep=''), value = TRUE))
if(length(stk.index.type)==0) stk.index.type <- NA
stk.index.distribution <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_distribution',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.distribution)==0) stk.index.distribution <- NA
stk.index.var <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_index.var.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.var)==0) stk.index.var <- NA
stk.index.q <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_index.q.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.q)==0) stk.index.q <- NA
stk.index.catch.n <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_catch.n.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.catch.n)==0) stk.index.catch.n <- NA
stk.index.catch.wt <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_catch.wt.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.catch.wt)==0) stk.index.catch.wt <- NA
stk.index.sel.pattern<- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_sel.pattern.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.sel.pattern)==0) stk.index.sel.pattern <- NA
stk.index.effort <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_effort.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.effort)==0) stk.index.effort <- NA
stk.index.range.min <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.min',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.min)==0) stk.index.range.min <- NA
stk.index.range.max <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.max',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.max)==0) stk.index.range.max <- NA
stk.index.range.startf <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.startf',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.startf)==0) stk.index.range.startf <- NA
stk.index.range.endf <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.endf',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.endf)==0) stk.index.range.endf <- NA
stk.index.range.plusgroup <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.plusgroup',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.plusgroup)==0) stk.index.range.plusgroup <- NA
stk.index.range.minyear <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.minyear',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.minyear)==0) stk.index.range.minyear <- NA
stk.index.range.maxyear <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.maxyear',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.maxyear)==0) stk.index.range.maxyear <- NA
stk.unit <- mget(grep(stks.data[[stk]],pattern=paste(stk,'.unit',sep=""), value = TRUE),envir=as.environment(1))
if(length(stk.unit)==0) stk.unit <- NA
#-----------------------------------------------------------------------------
# Section 2.2: Check dimensions
#-----------------------------------------------------------------------------
if(stk.index.type=="FLIndex"){
stk.flindex<- FLIndex(name = nm.stk.index, index = flqa)
}else{
stk.flindex<- FLIndexBiomass(name = nm.stk.index, index = flq)
flqa <- flq}
if(!all(is.na(stk.index.var))){
stk.index.var <- stk.index.var[[1]]}
if(!all(is.na(stk.index.q))){
stk.index.q <- stk.index.q[[1]]}
if(!all(is.na(stk.index.effort))){
stk.index.effort <- stk.index.effort[[1]]}
if(!all(is.na(stk.index.catch.n))){
stk.index.catch.n <- stk.index.catch.n[[1]]}
if(!all(is.na(stk.index.catch.wt))){
stk.index.catch.wt <- stk.index.catch.wt[[1]]}
if(!all(is.na(stk.index.sel.pattern))){
stk.index.sel.pattern <- stk.index.sel.pattern[[1]]}
if(!all(is.na(stk.index.range.min))){
stk.index.range.min <- stk.index.range.min[[1]]}
if(!all(is.na(stk.index.range.max))){
stk.index.range.max <- stk.index.range.max[[1]]}
if(!all(is.na(stk.index.range.startf))){
stk.index.range.startf <- stk.index.range.startf[[1]]}
if(!all(is.na(stk.index.range.endf))){
stk.index.range.endf <- stk.index.range.endf[[1]]}
if(!all(is.na(stk.index.range.plusgroup))){
stk.index.range.plusgroup <- stk.index.range.plusgroup[[1]]}
if(!all(is.na(stk.index.range.minyear))){
stk.index.range.minyear <- stk.index.range.minyear[[1]]}
if(!all(is.na(stk.index.range.maxyear))){
stk.index.range.maxyear <- stk.index.range.maxyear[[1]]}
log.dim <- equal.flq.Dimnames(lflq=list(stk.index,stk.flindex@index),1:2)
if(!log.dim)stop('in indices dimension \n')
stk.flindex@catch.n[] <- stk.index.catch.n
stk.flindex@effort[] <- stk.index.effort
stk.flindex@index.q[] <- stk.index.q
stk.flindex@index[] <- stk.index
stk.flindex@index.var[] <- stk.index.var
stk.flindex@sel.pattern[] <- stk.index.sel.pattern
stk.flindex@catch.wt[] <- stk.index.catch.wt
stk.flindex@range[['min']] <- stk.index.range.min
stk.flindex@range[['max']] <- stk.index.range.max
stk.flindex@range[['minyear']] <- stk.index.range.minyear
stk.flindex@range[['maxyear']] <- stk.index.range.maxyear
stk.flindex@range[['startf']] <- stk.index.range.startf
stk.flindex@range[['endf']] <- stk.index.range.endf
stk.flindex@range[['plusgroup']] <- stk.index.range.plusgroup
list.stk.index[[j]] <- stk.flindex
}
names(list.stk.index) <- nms.stk.index
indices[[stk]]<- FLIndices(list.stk.index)
}
return(indices)
}
}
flr/FLBEIA documentation built on July 14, 2024, 11:36 a.m.
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Defines functions create.indices.data
Documented in create.indices.data
###############################################################################
# AUTHOR(DATE): Agurtzane Urtizberea, Dorleta Garcia and Sonia Sanchez
# RESEARCH INSTITUTE: AZTI-TECNALIA
# TITLE: create.indices.data
# NOTE #1: Return a list with FLIndex objects
###############################################################################
#-------------------------------------------------------------------------
#'
#' FLBEIA easy conditioning: indices argument creator
#'
#' create.indices.data function creates an FLIndices object
#'
#' @param ni Number of iterations (number).
#' @param ns Number of seasons (number).
#' @param yrs A vector with c(first.yr,proj.yr, last.yr) where
#'\itemize{
#' \item first.yr: First year of simulation (number).
#' \item proj.yr: First year of projection (number).
#' \item last.yr: Last year of projection (number).}
#' @param stks.data A list with the names of the stocks with indices and the following elements:
#'\itemize{
#' \item stk.unit: Number of units of the stock (number).
#' \item stk.age.min: Minimum age class of the stock (number).
#' \item stk.age.max: Maximum age class of the stock (number).
#' \item stk_indices: Name of indices for the stock 'stk' (vector).
#' \item stk_ind_index.flq: Historical index data for index 'ind' of stock 'stk' (FLQuant).}
#' Optionals:
#'\itemize{
#' \item stk_ind_type: Type of index (character).
#' \item stk_ind_distribution: Name of the statistical distribution of the 'ind' index values for stock 'stk' (character).
#' \item stk_ind_index.var.flq: Variability in 'ind' index of stock 'stk' (FLQuant).
#' \item stk_ind_index.q.flq: Catchability for 'ind' index of stock 'stk' (FLQuant).
#' \item stk_ind_catch.n.flq: Catch at age in numbers for 'ind' index of stock 'stk'(FLQuant).
#' \item stk_ind_catch.wt.flq: Mean weight at age in the catch for 'ind' index of stock 'stk' (FLQuant).
#' \item stk_ind_effort.flq: Effort for 'ind' index of stock 'stk' (FLQuant).
#' \item stk_ind_sel.pattern.flq: Selection pattern for 'ind' index of stock 'stk' (FLQuant).
#' \item stk_ind_range.min: Minimum age in 'ind' index of stock 'stk' (number).
#' \item stk_ind_range.max: Maximum age in 'ind' index of stock 'stk' (number).
#' \item stk_ind_range.plusgroup: Plusgroup age in 'ind' index of stock 'stk' (number).
#' \item stk_ind_range.minyear: First year with 'ind' index data of stock 'stk' (number).
#' \item stk_ind_range.maxyear: Last year with 'ind' index data of stock 'stk' (number).
#' \item stk_ind_range.startf: Minimum age for calculating average fishing mortality for 'ind' index of stock 'stk' (number).
#' \item stk_ind_range.endf: Maximum age for calculating average fishing mortality for 'ind' index of stock 'stk' (number).}
#'
#' @return An FLIndices object.
#'
#
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
# Section 1: Is there any index data?
# Section 2: Create indices
# 2.1 Historical data per stock
# 2.2 Check dimensions
#-------------------------------------------------------------------------------
create.indices.data <- function(yrs,ns,ni,stks.data){
#==============================================================================
# Section 1: Is there any index data?
#==============================================================================
ind <- unlist(sapply(stks.data,function(x) grep(x, pattern="_indices",value=TRUE)))
nms.stks.index <- unique(sub('.*?^(.*?)_indices*', '\\1', ind))
indices <- NULL
if(length(nms.stks.index)==0){
cat("Warning:indices is NULL \n")
}else{
#==============================================================================
# Section 2: indices
#==============================================================================
n.stks.index <- length(nms.stks.index)
indices <- vector('list',n.stks.index)
names(indices) <- nms.stks.index
first.yr <- yrs[["first.yr"]]
proj.yr <- yrs[["proj.yr"]]
last.yr <- yrs[["last.yr"]]
proj.yrs <- as.character(proj.yr:last.yr)
hist.yrs <- as.character(first.yr:(proj.yr-1))
ny <- length(first.yr:last.yr)
list.stks.unit <- lapply(stks.data, function(ch) grep(pattern="unit", ch, value = TRUE))
list.stks.age <- lapply(stks.data, function(ch) grep(pattern="age", ch, value = TRUE))
list.stks.flqa <- create.list.stks.flqa(nms.stks.index,yrs,ni,ns,list.stks.unit,list.stks.age)
list.stks.flq <- create.list.stks.flq(nms.stks.index,yrs,ni,ns,list.stks.unit)
#-----------------------------------------------------------------------------
# Section 2.1: Historical data per stock
#-----------------------------------------------------------------------------
for (i in 1:n.stks.index){
stk <- nms.stks.index[i]
cat('=============', stk,'index','=============\n')
nms.stk.index <- get(grep(stks.data[[stk]],pattern="_indices", value = TRUE))
list.stk.index <- list()
for(j in 1:length(nms.stk.index)){
nm.stk.index <- nms.stk.index[j]
flqa <- list.stks.flqa[[stk]]
flq <- list.stks.flq[[stk]]
stk.index <- get(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_index.flq',sep=''), value = TRUE))
stk.index.type <- get(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_type',sep=''), value = TRUE))
if(length(stk.index.type)==0) stk.index.type <- NA
stk.index.distribution <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_distribution',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.distribution)==0) stk.index.distribution <- NA
stk.index.var <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_index.var.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.var)==0) stk.index.var <- NA
stk.index.q <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_index.q.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.q)==0) stk.index.q <- NA
stk.index.catch.n <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_catch.n.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.catch.n)==0) stk.index.catch.n <- NA
stk.index.catch.wt <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_catch.wt.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.catch.wt)==0) stk.index.catch.wt <- NA
stk.index.sel.pattern<- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_sel.pattern.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.sel.pattern)==0) stk.index.sel.pattern <- NA
stk.index.effort <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_effort.flq',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.effort)==0) stk.index.effort <- NA
stk.index.range.min <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.min',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.min)==0) stk.index.range.min <- NA
stk.index.range.max <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.max',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.max)==0) stk.index.range.max <- NA
stk.index.range.startf <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.startf',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.startf)==0) stk.index.range.startf <- NA
stk.index.range.endf <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.endf',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.endf)==0) stk.index.range.endf <- NA
stk.index.range.plusgroup <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.plusgroup',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.plusgroup)==0) stk.index.range.plusgroup <- NA
stk.index.range.minyear <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.minyear',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.minyear)==0) stk.index.range.minyear <- NA
stk.index.range.maxyear <- mget(grep(stks.data[[stk]],pattern=paste(stk,'_',nm.stk.index,'_range.maxyear',sep=''), value = TRUE),envir=as.environment(1))
if(length(stk.index.range.maxyear)==0) stk.index.range.maxyear <- NA
stk.unit <- mget(grep(stks.data[[stk]],pattern=paste(stk,'.unit',sep=""), value = TRUE),envir=as.environment(1))
if(length(stk.unit)==0) stk.unit <- NA
#-----------------------------------------------------------------------------
# Section 2.2: Check dimensions
#-----------------------------------------------------------------------------
if(stk.index.type=="FLIndex"){
stk.flindex<- FLIndex(name = nm.stk.index, index = flqa)
}else{
stk.flindex<- FLIndexBiomass(name = nm.stk.index, index = flq)
flqa <- flq}
if(!all(is.na(stk.index.var))){
stk.index.var <- stk.index.var[[1]]}
if(!all(is.na(stk.index.q))){
stk.index.q <- stk.index.q[[1]]}
if(!all(is.na(stk.index.effort))){
stk.index.effort <- stk.index.effort[[1]]}
if(!all(is.na(stk.index.catch.n))){
stk.index.catch.n <- stk.index.catch.n[[1]]}
if(!all(is.na(stk.index.catch.wt))){
stk.index.catch.wt <- stk.index.catch.wt[[1]]}
if(!all(is.na(stk.index.sel.pattern))){
stk.index.sel.pattern <- stk.index.sel.pattern[[1]]}
if(!all(is.na(stk.index.range.min))){
stk.index.range.min <- stk.index.range.min[[1]]}
if(!all(is.na(stk.index.range.max))){
stk.index.range.max <- stk.index.range.max[[1]]}
if(!all(is.na(stk.index.range.startf))){
stk.index.range.startf <- stk.index.range.startf[[1]]}
if(!all(is.na(stk.index.range.endf))){
stk.index.range.endf <- stk.index.range.endf[[1]]}
if(!all(is.na(stk.index.range.plusgroup))){
stk.index.range.plusgroup <- stk.index.range.plusgroup[[1]]}
if(!all(is.na(stk.index.range.minyear))){
stk.index.range.minyear <- stk.index.range.minyear[[1]]}
if(!all(is.na(stk.index.range.maxyear))){
stk.index.range.maxyear <- stk.index.range.maxyear[[1]]}
log.dim <- equal.flq.Dimnames(lflq=list(stk.index,stk.flindex@index),1:2)
if(!log.dim)stop('in indices dimension \n')
stk.flindex@catch.n[] <- stk.index.catch.n
stk.flindex@effort[] <- stk.index.effort
stk.flindex@index.q[] <- stk.index.q
stk.flindex@index[] <- stk.index
stk.flindex@index.var[] <- stk.index.var
stk.flindex@sel.pattern[] <- stk.index.sel.pattern
stk.flindex@catch.wt[] <- stk.index.catch.wt
stk.flindex@range[['min']] <- stk.index.range.min
stk.flindex@range[['max']] <- stk.index.range.max
stk.flindex@range[['minyear']] <- stk.index.range.minyear
stk.flindex@range[['maxyear']] <- stk.index.range.maxyear
stk.flindex@range[['startf']] <- stk.index.range.startf
stk.flindex@range[['endf']] <- stk.index.range.endf
stk.flindex@range[['plusgroup']] <- stk.index.range.plusgroup
list.stk.index[[j]] <- stk.flindex
}
names(list.stk.index) <- nms.stk.index
indices[[stk]]<- FLIndices(list.stk.index)
}
return(indices)
}
}
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