l2a.RdMethod to convert length-based data to age-based
l2a(object, model, ...)
# S4 method for FLQuant,a4aGr
l2a(
object,
model,
halfwidth = c(diff(as.numeric(dimnames(object)[[1]])),
tail(diff(as.numeric(dimnames(object)[[1]])), 1))/2,
stat = "sum",
max_age = NA
)
# S4 method for FLStockLen,a4aGr
l2a(object, model, plusgroup = NA, ...)
# S4 method for FLIndex,a4aGr
l2a(object, model, ...)an FLQuant, or FLStockLen object.
an a4aGr object
additional argument list that might never be used
the halfwidths of the length classes; a single numeric or vector the size of the number of length classes; not used if object is an FLStockLen
the aggregation statistic, which must be mean or sum; only used if object is an FLQuant.
the maximum age in the returned FLQuant; all ages above this are set to max_age; only used if object is an FLQuant
the plusgroup of the stock; only used if the object is an FLStockLen.
an age based FLQuant, FLStock
A deterministic slicing method converts the length-based data to age-based data, using the supplied growth model (the a4aGr object).
Each length-based observation is allocated to a corresponding age, based on the growth model, and aggregated accordingly (either the sum or the mean).
There should be 1 or n iterations in both the object being sliced and the growth model.
This means that although the slicing method is deterministic, the length-based data is sliced by each iteration of the growth parameters, thereby propagating the uncertainty in the biological growth parameters (representing process uncertainty) through to the age-based data.
# Southern hake
# Variance-covariance matrix for parameters
mm <- matrix(NA, ncol=3, nrow=3)
diag(mm) <- c(2310, 0.13, 0.84)
mm[upper.tri(mm)] <- mm[lower.tri(mm)] <- c(-7.22,-6.28,0.08)
# Make the von Bertalanffy growth model
md <- ~linf*(1-exp(-k*(t-t0)))
imd <- ~t0-1/k*log(1-len/linf)
prs <- FLPar(linf=130, k=0.164, t0=-0.092, units=c("cm","yr-1","yr"))
vbObj <- a4aGr(grMod=md, grInvMod=imd, params=prs, vcov=mm, distr="norm")
# Make a triangle copula for simulating process error
linf <- list(a=104.5, b=155.5, c=130)
k <- list(a=0.132, b=0.196, c=0.164)
t0 <- list(a=-0.184, b=0, c=-0.092)
tri_pars <- list(linf = linf, k = k, t0 = t0)
# Simulate 10 iterations from it
vbObj_tri <- mvrtriangle(10, vbObj, paramMargins=tri_pars)
#> Warning: margins correct? Currently, have no function(s) named: ptriangle
#> Warning: margins correct? Currently, have no function(s) named: dtriangle
#> Error in qtriangle(x, a = 104.5, b = 155.5, c = 130): could not find function "qtriangle"
data(southernHakeLen)
# Extract the catch numbers at length from stock object
cth <- catch.n(shake_len)
# Slice the data using the unsimulated growth object
# so the stock and the growth object have 1 iteration
cthA1 <- l2a(cth, vbObj)
# Slice with 1 iteration in stock and multiple in growth object
cthA2 <- l2a(cth, vbObj_tri)
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'model' in selecting a method for function 'l2a': object 'vbObj_tri' not found
# Result is age based catch with multiple iterations
# mod: iter=1, data: iter=n
cthA3 <- l2a(propagate(cth,10), vbObj)
# both with iter=n
cthA4 <- l2a(propagate(cth,10), vbObj_tri)
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'model' in selecting a method for function 'l2a': object 'vbObj_tri' not found
# converting a stock object
shake_age <- l2a(shake_len, vbObj)
#> Warning: Individual weights, M and maturity will be (weighted) averaged accross lengths,
#> harvest is not computed and everything else will be summed.
#> If this is not what you want, you'll have to deal with these slots by hand.
shake_age <- l2a(shake_len, vbObj_tri)
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'model' in selecting a method for function 'l2a': object 'vbObj_tri' not found
shake_age <- l2a(propagate(shake_len, 10), vbObj)
#> Warning: Individual weights, M and maturity will be (weighted) averaged accross lengths,
#> harvest is not computed and everything else will be summed.
#> If this is not what you want, you'll have to deal with these slots by hand.
shake_age <- l2a(propagate(shake_len, 10), vbObj_tri)
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'model' in selecting a method for function 'l2a': object 'vbObj_tri' not found
# converting a index object
index_pt_age <- l2a(index_pt_len, vbObj)
index_pt_age <- l2a(index_pt_len, mvrnorm(10, vbObj))
#> Warning: Some ages are less than 0, indicating a mismatch between input data lengths
#> and growth parameters (possibly t0)
#> Warning: Trimming age range to a minimum of 0
index_pt_age <- l2a(propagate(index_pt_len, 10), vbObj)