Example MSE object used in the vignette

Description

A dummy example MSE object, based on porgy, generic fleet and imprecise and unbiased observation model, four new MPs, and 20 simulations.

Usage

data("PorgMSE")

Format

The format is: Formal class 'MSE' [package "DLMtool"] with 17 slots ..@ Name : chr "Stock:Porgy Fleet:Generic_IncE Observation model:Imprecise_Unbiased" ..@ nyears : num 50 ..@ proyears: num 20 ..@ nMPs : int 4 ..@ MPs : chr [1:4] "AvC" "THC" "matlenlim" "area1_50" ..@ nsim : num 20 ..@ OM :'data.frame': 20 obs. of 34 variables: .. ..$ RefY : num [1:20] 44.8 101.2 119.9 84.3 126 ... .. ..$ M : num [1:20] 0.242 0.242 0.24 0.22 0.211 ... .. ..$ Depletion : num [1:20] 0.0791 0.37 0.5231 0.087 0.3618 ... .. ..$ A : num [1:20] 53.7 659.3 1074.2 240.2 281.7 ... .. ..$ BMSY_B0 : num [1:20] 0.429 0.419 0.421 0.394 0.414 ... .. ..$ FMSY_M : num [1:20] 0.217 0.243 0.194 0.404 0.22 ... .. ..$ Mgrad : num [1:20] 0.0556 0.0192 0.0365 0.08 -0.1671 ... .. ..$ Msd : num [1:20] 0.08302 0.02084 0.03384 0.03472 0.00318 ... .. ..$ procsd : num [1:20] 0.492 0.31 0.401 0.3 0.432 ... .. ..$ Esd : num [1:20] 0.391 0.194 0.194 0.366 0.38 ... .. ..$ dFfinal : num [1:20] 0.0276 0.0166 0.0156 0.0249 0.0181 ... .. ..$ MSY : num [1:20] 58.1 55.8 56.5 54.6 51.9 ... .. ..$ qinc : num [1:20] 0.501 -0.656 1.35 -1.478 1.554 ... .. ..$ qcv : num [1:20] 0.128 0.288 0.163 0.163 0.263 ... .. ..$ FMSY : num [1:20] 0.0526 0.059 0.0465 0.0889 0.0465 ... .. ..$ Linf : num [1:20] 53.5 51 50.2 51.2 51.7 ... .. ..$ K : num [1:20] 0.189 0.209 0.2 0.186 0.19 ... .. ..$ t0 : num [1:20] -1.02 -1.01 -1.04 -1.02 -1.01 ... .. ..$ hs : num [1:20] 0.397 0.408 0.383 0.459 0.366 ... .. ..$ Linfgrad : num [1:20] 0.0781 0.1421 0.1478 0.1272 0.0708 ... .. ..$ Kgrad : num [1:20] 0.0737 -0.1356 0.2391 -0.0225 -0.1415 ... .. ..$ Linfsd : num [1:20] 0.00464 0.01446 0.0104 0.00358 0.01344 ... .. ..$ recgrad : num [1:20] -6.94 -6.77 3.21 -8.52 1.53 ... .. ..$ Ksd : num [1:20] 0.00384 0.02322 0.00456 0.01538 0.01945 ... .. ..$ ageM : num [1:20] 1.47 2.59 3.16 2.75 3.15 ... .. ..$ V26 : num [1:20] 4.42 7.94 6.13 6 10.87 ... .. ..$ V27 : num [1:20] 21 20.3 24 23.1 24.7 ... .. ..$ V28 : num [1:20] 0.855 0.536 0.927 0.107 0.626 ... .. ..$ LFC : num [1:20] 12.4 12.1 12.3 12.3 13.6 ... .. ..$ OFLreal : num [1:20] 9.24 40.85 44.74 11.03 37.62 ... .. ..$ Spat_targ : num [1:20] 1 1 1 1 1 1 1 1 1 1 ... .. ..$ Frac_area_1 : num [1:20] 0.1034 0.1014 0.1038 0.0979 0.1012 ... .. ..$ Prob_staying: num [1:20] 0.976 0.976 0.937 0.986 0.926 ... .. ..$ AC : num [1:20] 0.322 0.614 0.761 0.478 0.31 ... ..@ Obs :'data.frame': 20 obs. of 25 variables: .. ..$ Cbias : num [1:20] 1.06 1.01 1 1.04 1.01 ... .. ..$ Csd : num [1:20] 0.55 0.399 0.288 0.406 0.373 ... .. ..$ CAA_nsamp : num [1:20] 92 53 83 70 76 68 71 95 79 76 ... .. ..$ CAA_ESS : num [1:20] 14 19 11 19 14 19 20 13 18 16 ... .. ..$ CAL_nsamp : num [1:20] 90 66.6 86.8 58.2 65.1 ... .. ..$ CAL_ESS : num [1:20] 15 17 16 13 12 15 13 18 13 17 ... .. ..$ Isd : num [1:20] 0.439 0.563 0.571 0.21 0.512 ... .. ..$ Dbias : num [1:20] 1.038 0.936 0.77 0.873 0.846 ... .. ..$ Derr : num [1:20] 0.1293 0.1501 0.0756 0.1422 0.0647 ... .. ..$ Mbias : num [1:20] 0.935 1.048 0.986 1.009 1.028 ... .. ..$ FMSY_Mbias : num [1:20] 1.121 0.768 0.881 1.063 0.862 ... .. ..$ BMSY_B0bias: num [1:20] 1.056 0.978 0.781 1.111 0.819 ... .. ..$ lenMbias : num [1:20] 1.041 0.939 1.029 1.019 1.02 ... .. ..$ LFCbias : num [1:20] 0.898 1.007 0.903 0.989 0.973 ... .. ..$ LFSbias : num [1:20] 0.971 1.013 1.059 1.027 1.034 ... .. ..$ Abias : num [1:20] 1.045 1.079 0.525 0.826 2.767 ... .. ..$ Aerr : num [1:20] 0.423 0.211 0.499 0.493 0.299 ... .. ..$ Kbias : num [1:20] 1.056 0.979 0.939 1.01 1.019 ... .. ..$ t0bias : num [1:20] 0.994 0.943 0.985 0.993 0.995 ... .. ..$ Linfbias : num [1:20] 0.93 1.04 1.076 0.944 0.994 ... .. ..$ hbias : num [1:20] 0.961 0.925 1.028 1.054 1.002 ... .. ..$ Irefbias : num [1:20] 1.117 0.979 0.869 1.027 1.146 ... .. ..$ Crefbias : num [1:20] 0.969 1.137 0.873 1.035 0.941 ... .. ..$ Brefbias : num [1:20] 1.015 1.015 0.871 1.023 1.004 ... .. ..$ betas : num [1:20] 0.967 0.815 0.813 1.357 0.74 ... ..@ B_BMSY : num [1:20, 1:4, 1:20] 0.113 0.644 0.516 0.171 0.581 ... ..@ F_FMSY : num [1:20, 1:4, 1:20] 8.68 1.68 1.62 5.01 1.99 ... ..@ B : num [1:20, 1:4, 1:20] 135 783 665 190 804 ... ..@ FM : num [1:20, 1:4, 1:20] 0.4565 0.0988 0.0752 0.4454 0.0923 ... ..@ C : num [1:20, 1:4, 1:20] 73.9 65.2 50.1 61.6 64.1 ... ..@ TAC : num [1:20, 1:4, 1:20] 73.9 65.2 50.1 61.6 64.1 ... ..@ SSB_hist: num [1:20, 1:34, 1:50, 1:2] 2.37 2.28 1.18 1.48 1.64 ... ..@ CB_hist : num [1:20, 1:34, 1:50, 1:2] 0 0 0 0 0 0 0 0 0 0 ... ..@ FM_hist : num [1:20, 1:34, 1:50, 1:2] 0 0 0 0 0 0 0 0 0 0 ...

Examples

data(PorgMSE)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(DLMtool)
Loading required package: snowfall
Loading required package: snow
Loading required package: boot
Loading required package: MASS
Loading required package: parallel

Attaching package: 'parallel'

The following objects are masked from 'package:snow':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, clusterSplit, makeCluster, parApply,
    parCapply, parLapply, parRapply, parSapply, splitIndices,
    stopCluster

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/DLMtool/PorgMSE.Rd_%03d_medium.png", width=480, height=480)
> ### Name: PorgMSE
> ### Title: Example MSE object used in the vignette
> ### Aliases: PorgMSE
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(PorgMSE)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>