This function calculates various length-based indicators for fish stock assessment using length frequency data and bootstrap resampling.
FishPar(data, resample, progress)
A data frame containing two columns: Length and Frequency.
An integer indicating the number of bootstrap resamples.
A logical value indicating whether to display progress.
A list containing estimated length parameters, Froese indicators, and other relevant metrics.
data <- data.frame(Length = c(10, 20, 30, 40, 50), Frequency = c(5, 10, 15, 20, 25))
FishPar(data, 100, progress = FALSE)
#> Warning: span too small. fewer data values than degrees of freedom.
#> Warning: pseudoinverse used at 9.8
#> Warning: neighborhood radius 20.2
#> Warning: reciprocal condition number 0
#> Warning: There are other near singularities as well. 408.04
#> $estimated_length_par
#> Parameter Mean_estimate Lower_CI Upper_CI
#> 1 Lmax 44.60000 30.00000 50.00000
#> 2 Linf 46.94737 31.57895 52.63158
#> 3 Lmat 26.43348 18.53998 29.32967
#> 4 Lopt 27.62597 19.00286 30.80168
#> 5 Lopt_p10 30.38857 20.90314 33.88185
#> 6 Lopt_m10 24.86337 17.10257 27.72151
#>
#> $estimated_froese_par
#> Parameter Estimate
#> 1 Pmat 46.66667
#> 2 Popt 20.00000
#> 3 Pmega 26.66667
#>
#> $estimated_freq_par
#> Parameter Estimate
#> 1 sumT 75
#> 2 sum_mat 35
#> 3 sum_opt 15
#> 4 sum_mega 20
#>
#> $forese_ind_vs_target
#> Parameters Froese_catch Froese_tar
#> 1 Pmat 46.66667 100
#> 2 Popt 20.00000 100
#> 3 Pmega 26.66667 20
#>
#> $LM_ratio
#> [1] 0.9568343
#>
#> $Pobj
#> [1] 93.33333
#>