Bhattacharya: Bhattacharya

In PabloMBooster/fenix: fenix

Bhattacharya

Description

Analyzes the length frequeney distributions. The middle lengths obtained for each length group

Usage

Bhattacharya(x, length_class = seq(5, 20, by = 0.5), groups, mu = NULL, maxit = 5000)

Arguments

x	length frequency
length_class	length class
groups	number of groups that you want to separate
mu	starting value of vector of groups means
maxit	the maximum number of iterations

Details

If necessary, install mixtools package.

Examples

# Sample (Peruvian anchovy)
sample_frequency <- c(0,0,0,0,0,0,0,0,0,2,7,14,22,15,13,12,17,22,35,28,7,4,1,0,0,0,0,0,0,0,0)
length <- seq(5,20, by = 0.5)

# identify groups
view_modas <- modas(matrix(sample_frequency, nrow = 1), Lmin = 5, Lmax = 20, dL = 0.5, umbral = 10) 

# number of groups
num_modas = apply(view_modas, 1, unique_modas)


# weighted
catch_frequency = weighted_frequency(length = length, frequency = sample_frequency, a = 0.003925, b = 3.2178, catch =  50000) 
plot(length, catch_frequency, type = "l", lwd = 2, ylab = "Catch (number of individuals)", xlab = "Length (cm)")

# bhattacharya
out_cohortes = Bhattacharya(x = catch_frequency, groups = num_modas) 


# rebuild the cohorts
cohortes <- NULL
for(i in 1:length(out_cohortes$tableBhatt$Population)){
  N = out_cohortes$tableBhatt$Population[i]
  L = out_cohortes$tableBhatt$Mean[i]
  S = out_cohortes$outL$sigma[i]

  cohortei = cohort_to_length(cohort = c(N, L, S), lower = 5, upper = 20) 
  cohortes = rbind(cohortes, cohortei)
}

# plots
plot(length, catch_frequency, type = "l", lwd = 2, ylab = "Catch (number of individuals)", xlab = "Length (cm)")
lines(length, cohortes[1,], col = 2, lty = 2)
lines(length, cohortes[2,], col = 2, lty = 2)

PabloMBooster/fenix documentation built on Oct. 21, 2023, 8:22 p.m.