A class for modelling abundance indices.

FLIndex(object, ...)

# S4 method for FLQuant
FLIndex(object, plusgroup = dims(object)$max, ...)

# S4 method for missing
FLIndex(object, ...)

Details

The FLIndex object holds data and parameters related to abundance indices.

Slots

type

Type of index (character).

distribution

Statistical distribution of the index values (character).

index

Index values (FLQuant).

index.var

Variance of the index (FLQuant).

catch.n

Catch numbers used to create the index (FLQuant).

catch.wt

Catch weight of the index (FLQuant).

effort

Effort used to create the index (FLQuant).

sel.pattern

Selection pattern for the index (FLQuant).

index.q

Catchability of the index (FLQuant).

name

Name of the stock (character).

desc

General description of the object (character).

range

Named numeric vector containing the quant and year ranges, the plusgroup, and the period of the year, expressed as proportions of a year, that corresponds to the index (numeric).

See also

Examples

# Create an FLIndex object. fli <- FLIndex(index=FLQuant(rnorm(8), dim=c(1,8)), name="myTestFLindex") summary(fli)
#> An object of class "FLIndex" #> #> Name: myTestFLindex #> Description: #> Type : #> Distribution : #> Quant: quant #> Dims: quant year unit season area iter #> 1 8 1 1 1 1 #> #> Range: min max pgroup minyear maxyear startf endf #> NA NA NA 1 8 NA NA #> #> index : [ 1 8 1 1 1 1 ], units = NA #> index.var : [ 1 8 1 1 1 1 ], units = NA #> catch.n : [ 1 8 1 1 1 1 ], units = NA #> catch.wt : [ 1 8 1 1 1 1 ], units = NA #> effort : [ 1 8 1 1 1 1 ], units = NA #> sel.pattern : [ 1 8 1 1 1 1 ], units = NA #> index.q : [ 1 8 1 1 1 1 ], units = NA
index(fli)
#> An object of class "FLQuant" #> , , unit = unique, season = all, area = unique #> #> year #> quant 1 2 3 4 5 6 7 8 #> all -0.17409 -0.22174 -1.00953 0.48073 1.60441 -1.51502 -1.41602 0.87678 #> #> units: NA
# Creat an FLIndex object using an existing FLQuant object. data(ple4) # Create a perfect index of abundance from abundance at age fli2 <- FLIndex(index=stock.n(ple4)) # Add some noise around the signal index(fli2) <- index(fli2)*exp(rnorm(1, index(fli2)-index(fli2), 0.1))