Calculate the relative error (RE; \([EM - OM]/OM\)) of
parameters and derived quantities stored in a scalar or time series
data frame generated by get_results_all().
calculate_re(dat, add = TRUE, EM = "em")An input data frame. Should be either a scalar or time series
data frame as returned from get_results_all() or a related
get_results_*(). Specifically, the data frame needs to have columns
with _em and _om as names. If the data is provided in long
rather than wide format, then convert_to_wide() will be used
internally before calculating RE and a wide data frame will be returned.
Logical: should the relative error columns be added to dat
or should the original EM and OM columns be dropped? If FALSE, then
the returned data frame will have only the identifying columns and the new
relative error columns. You could then merge selected columns back into
dat if you wished. The default is to return all columns.
A character value specifying the name of the EM to calculate the
RE of when the results are provided in long format and there is the potential
for multiple EMs. See the column model_run for options.
The default is to return a data frame structured the same as the
input data frame, i.e., dat, but with additional columns, where
'_re' is appended to the base string of the column name.
All NAN and Inf values are returned as NA values,
typically because you cannot divide by zero. Irrelevant columns, i.e.,
columns of entirely zero of NA are removed prior to returning the
data frame.
# Example with built in package data:
data("ts_dat", package = "ss3sim")
data("scalar_dat", package = "ss3sim")
head(calculate_re(ts_dat))
#> Warning: number of columns of result is not a multiple of vector length (arg 1)
#> year iteration scenario SpawnBio_om Recruit_0_om F._1_om SPRratio_om
#> 1 1 1 D0-E0-F0-cod 4084180000 166353000 0 1.11022e-16
#> 2 1 1 D0-E1-F0-cod 4084180000 166353000 0 1.11022e-16
#> 3 1 1 D1-E0-F0-cod 4084180000 166353000 0 1.11022e-16
#> 4 1 1 D1-E1-F0-cod 4084180000 166353000 0 1.11022e-16
#> 5 1 1 D1-E100-F0-cod 4084180000 132223000 0 1.11022e-16
#> 6 1 1 D1-E101-F0-M1-cod 4084180000 132223000 0 1.11022e-16
#> rec_dev_om raw_rec_dev_om SpawnBio_em Recruit_0_em F._1_em SPRratio_em
#> 1 2.29622e-01 0.229622 NA NA NA NA
#> 2 2.29622e-01 0.229622 NA NA NA NA
#> 3 2.29622e-01 0.229622 NA NA NA NA
#> 4 2.29622e-01 0.229622 NA NA NA NA
#> 5 -1.11022e-16 0.000000 NA NA NA NA
#> 6 -1.11022e-16 0.000000 NA NA NA NA
#> rec_dev_em raw_rec_dev_em ID D E F c species F._1_re
#> 1 NA NA D0-E0-F0-cod-1 D0 E0 F0 cod D0 NA
#> 2 NA NA D0-E1-F0-cod-1 D0 E1 F0 cod D0 NA
#> 3 NA NA D1-E0-F0-cod-1 D1 E0 F0 cod D1 NA
#> 4 NA NA D1-E1-F0-cod-1 D1 E1 F0 cod D1 NA
#> 5 NA NA D1-E100-F0-cod-1 D1 E100 F0 cod D1 NA
#> 6 NA NA D1-E101-F0-M1-cod-1 D1 E101 F0 M1 cod NA
#> Recruit_0_re SPRratio_re SpawnBio_re raw_rec_dev_re rec_dev_re
#> 1 NA NA NA NA NA
#> 2 NA NA NA NA NA
#> 3 NA NA NA NA NA
#> 4 NA NA NA NA NA
#> 5 NA NA NA NA NA
#> 6 NA NA NA NA NA
head(calculate_re(ts_dat, add = FALSE))
#> Warning: number of columns of result is not a multiple of vector length (arg 1)
#> year iteration scenario ID D E F c species
#> 1 1 1 D0-E0-F0-cod D0-E0-F0-cod-1 D0 E0 F0 cod D0
#> 2 1 1 D0-E1-F0-cod D0-E1-F0-cod-1 D0 E1 F0 cod D0
#> 3 1 1 D1-E0-F0-cod D1-E0-F0-cod-1 D1 E0 F0 cod D1
#> 4 1 1 D1-E1-F0-cod D1-E1-F0-cod-1 D1 E1 F0 cod D1
#> 5 1 1 D1-E100-F0-cod D1-E100-F0-cod-1 D1 E100 F0 cod D1
#> 6 1 1 D1-E101-F0-M1-cod D1-E101-F0-M1-cod-1 D1 E101 F0 M1 cod
#> F._1_re Recruit_0_re SPRratio_re SpawnBio_re raw_rec_dev_re rec_dev_re
#> 1 NA NA NA NA NA NA
#> 2 NA NA NA NA NA NA
#> 3 NA NA NA NA NA NA
#> 4 NA NA NA NA NA NA
#> 5 NA NA NA NA NA NA
#> 6 NA NA NA NA NA NA
head(calculate_re(scalar_dat, add = FALSE))
#> Warning: number of columns of result is not a multiple of vector length (arg 1)
#> iteration scenario max_grad
#> 1 1 D0-E0-F0-cod 7.67430e-05
#> 2 1 D0-E1-F0-cod 2.37825e-05
#> 3 1 D1-E0-F0-cod 1.95268e-05
#> 4 1 D1-E1-F0-cod 1.81203e-06
#> 5 1 D1-E100-F0-cod 1.16221e-03
#> 6 1 D1-E101-F0-M1-cod 5.24402e-04
#> version
#> 1 3.30.15.03-safe;_2020_04_23;_Stock_Synthesis_by_Richard_Methot_(NOAA)_using_ADMB_12.0
#> 2 3.30.15.03-safe;_2020_04_23;_Stock_Synthesis_by_Richard_Methot_(NOAA)_using_ADMB_12.0
#> 3 3.30.15.03-safe;_2020_04_23;_Stock_Synthesis_by_Richard_Methot_(NOAA)_using_ADMB_12.0
#> 4 3.30.15.03-safe;_2020_04_23;_Stock_Synthesis_by_Richard_Methot_(NOAA)_using_ADMB_12.0
#> 5 3.30.15.03-safe;_2020_04_23;_Stock_Synthesis_by_Richard_Methot_(NOAA)_using_ADMB_12.0
#> 6 3.30.15.03-safe;_2020_04_23;_Stock_Synthesis_by_Richard_Methot_(NOAA)_using_ADMB_12.0
#> RunTime hessian Niterations ID D E F c species
#> 1 2.350000 TRUE 856 D0-E0-F0-cod-1 D0 E0 F0 cod D0
#> 2 2.383333 TRUE 847 D0-E1-F0-cod-1 D0 E1 F0 cod D0
#> 3 2.266667 TRUE 888 D1-E0-F0-cod-1 D1 E0 F0 cod D1
#> 4 2.383333 TRUE 853 D1-E1-F0-cod-1 D1 E1 F0 cod D1
#> 5 2.783333 TRUE 1038 D1-E100-F0-cod-1 D1 E100 F0 cod D1
#> 6 3.066667 TRUE 1184 D1-E101-F0-M1-cod-1 D1 E101 F0 M1 cod
#> CV_old_Fem_GP_1_re CV_young_Fem_GP_1_re F_Btgt_re F_MSY_re
#> 1 -0.030213 0.00639 -0.005866500 -0.006625248
#> 2 -0.040172 0.01017 0.045775844 0.045806350
#> 3 -0.031768 0.00671 -0.006018545 -0.006791976
#> 4 -0.040306 0.00997 0.039775667 0.039690061
#> 5 -0.034361 0.06341 0.008429841 0.009582478
#> 6 -0.047358 0.06778 0.053929147 0.055757384
#> F_SPR_re ForeRecr_101_re L_at_Amax_Fem_GP_1_re L_at_Amin_Fem_GP_1_re
#> 1 -0.006018964 -1 0.011840909 -0.009695
#> 2 0.045501802 -1 0.014810606 -0.009720
#> 3 -0.006175300 -1 0.012151515 -0.009515
#> 4 0.039506289 -1 0.014727273 -0.009560
#> 5 0.008692322 NA -0.009219697 -0.027900
#> 6 0.054084688 NA -0.006181818 -0.027680
#> NatM_p_1_Fem_GP_1_re Recr_Unfished_re Ret_Catch_MSY_re SPR_MSY_re
#> 1 0.000000 -0.03589391 -0.027885388 4.734914e-04
#> 2 0.067805 0.10930776 0.024925079 -1.264176e-04
#> 3 0.000000 -0.05170054 -0.043722437 4.803869e-04
#> 4 0.060085 0.07695333 0.004872938 -4.597004e-05
#> 5 0.000000 0.08562050 0.082243013 -6.987446e-04
#> 6 0.059420 0.23094318 0.137861511 -1.156146e-03
#> SR_LN_R0_re SR_sigmaR_re SSB_Btgt_re SSB_MSY_re SSB_SPR_re SSB_Unfished_re
#> 1 -0.001957219 0 -0.02189549 -0.02123443 -0.02190055 -0.02189913
#> 2 0.005545455 0 -0.02149149 -0.02167873 -0.02149336 -0.02149513
#> 3 -0.002839572 0 -0.03768815 -0.03702450 -0.03768523 -0.03768688
#> 4 0.003962567 0 -0.03489077 -0.03495818 -0.03489078 -0.03489317
#> 5 0.004395722 399 0.07303189 0.07194742 0.07303111 0.07303302
#> 6 0.011112299 399 0.07775132 0.07593901 0.07774974 0.07774878
#> Size_DblN_ascend_se_Fishery_1_re Size_DblN_ascend_se_Survey_2_re
#> 1 0.0074862745 0.06768269
#> 2 0.0089411765 0.06543654
#> 3 0.0079019608 0.06758462
#> 4 0.0091039216 0.06545577
#> 5 -0.0015039216 0.13811154
#> 6 0.0004705882 0.13272885
#> Size_DblN_peak_Fishery_1_re Size_DblN_peak_Survey_2_re SmryBio_Unfished_re
#> 1 0.0074350394 0.02869617 -0.02197661
#> 2 0.0099094488 0.03014833 -0.02073907
#> 3 0.0078602362 0.02885167 -0.03776553
#> 4 0.0099704724 0.02999761 -0.03424256
#> 5 -0.0005511811 0.04370335 0.07303654
#> 6 0.0023129921 0.04472010 0.07855075
#> TotYield_Btgt_re TotYield_MSY_re TotYield_SPR_re Totbio_Unfished_re
#> 1 -0.02779283 -0.027885388 -0.027961646 -0.02198128
#> 2 0.02490518 0.024925079 0.024955677 -0.02069312
#> 3 -0.04362871 -0.043722437 -0.043801263 -0.03776969
#> 4 0.00487021 0.004872938 0.004889301 -0.03420418
#> 5 0.08208551 0.082243013 0.082375820 0.07304328
#> 6 0.13759112 0.137861511 0.138096670 0.07860665
#> VonBert_K_Fem_GP_1_re depletion_re first_yr_full_re last_yr_full_re
#> 1 -0.017750 -0.14981259 25 -0.01
#> 2 -0.022075 -0.02821320 25 -0.01
#> 3 -0.018375 -0.28698960 25 -0.01
#> 4 -0.022100 -0.14806637 25 -0.01
#> 5 0.022810 -0.08932675 25 -0.01
#> 6 0.017800 0.01485512 25 -0.01
rm("ts_dat", "scalar_dat")
#> Warning: object 'ts_dat' not found
#> Warning: object 'scalar_dat' not found