TropFishR (version 1.6.4)

ELEFAN_SA: ELEFAN_SA

Description

Electronic LEngth Frequency ANalysis with simulated annealing for estimating growth parameters.

Usage

ELEFAN_SA(
  lfq,
  seasonalised = FALSE,
  init_par = list(Linf = 50, K = 0.5, t_anchor = 0.5, C = 0, ts = 0),
  low_par = NULL,
  up_par = NULL,
  SA_time = 60 * 1,
  maxit = NULL,
  nb.stop.improvement = NULL,
  SA_temp = 1e+05,
  verbose = TRUE,
  MA = 5,
  addl.sqrt = FALSE,
  agemax = NULL,
  flagging.out = TRUE,
  plot = FALSE,
  plot.score = TRUE
)

Value

A list with the input parameters and following list objects:

• rcounts: restructured frequencies,

• peaks_mat: matrix with positive peaks with distinct values,

• ASP: available sum of peaks, sum of posititve peaks which could be potential be hit by growth curves,

• ncohort: maximum age of species,

• agemax: maximum age of species,

• par: a list with the parameters of the von Bertalanffy growth function:

  • Linf: length infinity in cm,

  • K: curving coefficient;

  • t_anchor: time point anchoring growth curves in year-length coordinate system, corrsponds to peak spawning month,

  • C: amplitude of growth oscillation (if seasonalised = TRUE),

  • ts: summer point of oscillation (ts = WP - 0.5) (if seasonalised = TRUE),

  • phiL: growth performance index defined as phiL = log10(K) + 2 * log10(Linf);

• Rn_max: highest score value (absolute value of cost function, comparable with ELEFAN and ELEFAN_GA).

Arguments

lfq

a list consisting of following parameters:

• midLengths midpoints of the length classes,

• dates dates of sampling times (class Date),

• catch matrix with catches/counts per length class (row) and sampling date (column);

seasonalised

logical; indicating if the seasonalised von Bertalanffy growth function should be applied (default: FALSE).

init_par

a list providing the Initial values for the components to be optimized. When set to NULL the following default values are used:

• Linf length infinity in cm (default is the maximum length class in the data),

• K curving coefficient (default: 0.5),

• t_anchor time point anchoring growth curves in year-length coordinate system, corrsponds to peak spawning month (range: 0 to 1, default: 0.5),

• C amplitude of growth oscillation (range: 0 to 1, default: 0),

• ts summer point (ts = WP - 0.5) (range: 0 to 1, default: 0);

low_par

a list providing the lower bounds for components. When set to NULL the following default values are used:

• Linf length infinity in cm (default is calculated from maximum length class in the data),

• K curving coefficient (default: 0.01),

• t_anchor time point anchoring growth curves in year-length coordinate system, corrsponds to peak spawning month (range: 0 to 1, default: 0),

• C amplitude of growth oscillation (range: 0 to 1, default: 0),

• ts summer point (ts = WP - 0.5) (range: 0 to 1, default: 0);

up_par

a list providing the upper bounds for components. When set to NULL the following default values are used:

• Linf length infinity in cm (default is calculated from maximum length class in the data),

• K curving coefficient (default: 0.01),

• t_anchor time point anchoring growth curves in year-length coordinate system, corrsponds to peak spawning month (range: 0 to 1, default: 0),

• C amplitude of growth oscillation (range: 0 to 1, default: 0),

• ts summer point (ts = WP - 0.5) (range: 0 to 1, default: 0);

SA_time

numeric; Maximum running time in seconds (default : 60 * 1).

maxit

Integer. Maximum number of iterations of the algorithm. Default is NULL.

nb.stop.improvement

Integer. The program will stop when there is no any improvement in 'nb.stop.improvement' steps. Default is NULL

SA_temp

numeric; Initial value for temperature (default : 1e5).

verbose

logical; TRUE means that messages from the algorithm are shown (default : TRUE).

MA

number indicating over how many length classes the moving average should be performed (defalut: 5, for more information see lfqRestructure).

addl.sqrt

Passed to lfqRestructure. Applied an additional square-root transformation of positive values according to Brey et al. (1988). (default: FALSE, for more information see lfqRestructure).

agemax

maximum age of species; default NULL, then estimated from Linf

flagging.out

logical; passed to lfqFitCurves. Default is TRUE

plot

logical; Plot restructured counts with fitted lines using plot.lfq and lfqFitCurves (default : FALSE).

plot.score

logical; Plot simulated annealing score progression. (Default: plot.score=TRUE)

Details

A more detailed description of the simulated annealing (SA) can be found in Xiang et al. (2013). The score value cost_value is not comparable with the score value of the other ELEFAN functions (ELEFAN or ELEFAN_GA).

References

Brey, T., Soriano, M., and Pauly, D. 1988. Electronic length frequency analysis: a revised and expanded user's guide to ELEFAN 0, 1 and 2.

Pauly, D. and N. David, 1981. ELEFAN I, a BASIC program for the objective extraction of growth parameters from length-frequency data. Meeresforschung, 28(4):205-211

Xiang, Y., Gubian, S., Suomela, B., & Hoeng, J. (2013). Generalized simulated annealing for global optimization: the GenSA Package. R Journal, 5(1), 13-28.

Examples

# \donttest{
## synthetic lfq data example
data(synLFQ4)
plot(synLFQ4, Fname="catch")

# ELEFAN_SA (takes approximately 2 minutes)
output <- ELEFAN_SA(synLFQ4, SA_time = 60*2, seasonalised = TRUE, MA = 11,
  init_par = list(Linf = 75, K = 0.5, t_anchor = 0.5, C = 0.5, ts = 0.5),
  low_par = list(Linf = 70, K = 0.3, t_anchor = 0, C = 0, ts = 0),
  up_par = list(Linf = 90, K = 0.7, t_anchor = 1, C = 1, ts = 1))
output$par
output$Rn_max

# view fit
plot(output)

# or
plot(output, draw = FALSE)
lfqFitCurves(output, col=1, par=output$par, draw=TRUE)$ESP

# compare to original parameters
tmp <- lfqFitCurves(output, col=4, lty=1,
   par=list(Linf=80, K=0.5, t_anchor=0.25, C=0.75, ts=0.5), draw=TRUE)
tmp$fESP
output$Rn_max
# }