hoenig(Ak, fik, fiz, threshold = 1, maxiter = 2000, age_classes = colnames(Ak[[1]]), length_classes = rownames(Ak[[1]]), name = "", description = "")k equally dimensioned
matrices, so that A[[k]][i, j] is the count of
individuals of length i and age j on sample
k.k vectors of equal length
(i), so that fik[[k]][i] is the total
number of fish in the length-class i on the
population from which Ak[[k]] was sampled.i)
where fiz[[z]][i] is the number of fish in the
length-class i on population z, for which
no age data is available.ALKr objects, one for each item in the
fiz list, each containing a matrix with the
probability of an individual of age j having length
i, i.e. $P(i|j)$, the vectors of age and length
classes, and information about the method used to generate
the key.
The returned ALKr object contains information on the
convergence threshold that was used, the number of
iterations ran, and if convergence was reached.
Convergence
The method proposed by Hoenig et al. (1993, 1994) is based on the EM algorithm as defined by Dempster et al. (1997), and it generates the ALK by a series of iterations which are repeated until convergence is acheived.
Let Nz be a list of matrices containing the number
of fish in each length and age class for each of the
z populations with unknown age information and with
length distribution specified by fiz. Convergence is
tested by evaluating the greatest of the absolute
differences between all pairs of Nz matrices
generated on the current and previous iterations:
max(mapply("-", Nz, Nz.old)).
10.2307/2984875Hoenig, J.M., Heisey, D.M., Hanumara, R.C. (1993). Using Prior and Current Information to Estimate Age Composition: a new kind of age-length key. ICES CM Documents 1993, 10.
Hoenig, J.M., Heisey, D.M., Hanumara, R.C. (1994). A computationally simple approach to using current and past data in age-length key. ICES CM Documents 1994, 5.
data(hom)
hoenig(Ak = hom$otoliths[1:10],
fik = replicate(10, hom$F1992, simplify = FALSE),
fiz = list(hom$F1993))
Run the code above in your browser using DataLab