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PIFSCstockassessments / TMB.LBSPR

Implementation of GTG LBSPR model using TMB
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Example Dataset Documentaion #9

Open efletcherPIFSC opened 5 years ago

efletcherPIFSC commented 5 years ago

Checking TMB.LBSPR give a WARNING for missing dataset documentation:

* checking for missing documentation entries ... WARNING
Undocumented code objects:
  'Example'
Undocumented data sets:
  'Example'
All user-level objects in a package should have documentation entries.
See chapter 'Writing R documentation files' in the 'Writing R
Extensions' manual.

In reference to: http://r-pkgs.had.co.nz/data.html#documenting-data

I like to cover:

The data object Example:

> str(Example)
Classes ‘data.table’ and 'data.frame':  25 obs. of  160 variables:
 $ Species     : chr  "CHMC" NA NA NA ...
    - Character string for species name
 $ Family      : chr  "Scaridae" NA NA NA ...
    - Family-level taxonomic name. Important to use correct spelling if calling "StepwiseLH" for life history data.
 $ LH.source   : chr  "Study" NA NA NA ...
     - Either "Study" or "Stepwise". Study=life history parameters inputted directly. Stepwise=Provide an Lmax value and obtained life history paramater esitmates through StepwiseLH package.
 $ Par         : chr  "Lmax" "Linf" "CVLinf" "K" ...
      - Name of the model parameter.
 $ Val1        : num  NA 457 0.101 0.34 -0.097 ...
      - First parameter of a probability distribution describing the corresponding parameter (e.g. mean)
 $ Val2        : num  NA 24 0.00795 0.04 NA ...
      - Second parameter of a probability distribution describing the corresponding paramter (e.g. SD).
 $ Dist        : chr  NA "Normal" "Normal" "Normal" ...
      - Name of the probability distribution to be used  (e.g. "Normal")
 $ Min         : num  NA 0 0.05 0.05 NA NA 0 NA 1 NA ...
     - Minimum bound for this parameter.
 $ Max         : num  NA 1500 0.2 1 NA NA 1200 NA 100 NA ...
     - Maximum bound for this parameter.
 $ Length_obs  : num  165 180 195 210 225 240 255 270 285 300 ...
     -Lower edge of the size bins use to classify length observations.
 $ Count_obs1  : num  0.78 0.39 4.27 0.78 0 ...
     - Counts or proportion of individual fish in a length bin. The following columns are simply bootstrap iterations of abundance-at-length data to incorporate uncertainty in length data into the model.
 $ Count_obs2  : num  0.39 0.39 9.76 0.61 0 ...
 $ Count_obs3  : num  0.39 0.78 4.27 1 0.61 ...
 $ Count_obs4  : num  0 0.78 4.88 1 0.61 ...
 $ Count_obs5  : num  0.39 1.17 6.71 2.83 1.22 ...
 $ Count_obs6  : num  0.39 1.17 9.76 0.61 0 ...
 $ Count_obs7  : num  0.78 0.39 6.1 0.61 0 ...
 $ Count_obs8  : num  0.39 0.78 6.71 0 0.61 ...
 $ Count_obs9  : num  0.39 0.78 9.15 1.61 0.61 ...
 $ Count_obs10 : num  0.39 2.34 6.1 0 1.22 ...
 $ Count_obs11 : num  0 0.78 3.05 0.39 1.22 ...
 $ Count_obs12 : num  0 0.78 4.88 0.39 1.22 ...
 $ Count_obs13 : num  0 1.17 3.66 0.39 0.61 ...
 $ Count_obs14 : num  0.39 0.39 4.27 0.78 0.61 ...
 $ Count_obs15 : num  0 1.95 9.15 1.22 0.61 ...
 $ Count_obs16 : num  0.78 0.39 4.88 1.22 0 ...
 $ Count_obs17 : num  0.39 0.39 6.71 1 0 ...
 $ Count_obs18 : num  0 1.56 9.15 1.22 0.61 ...
 $ Count_obs19 : num  0 0 6.71 1.61 0.61 ...
 $ Count_obs20 : num  0 1.17 9.15 0 0 ...
 $ Count_obs21 : num  0.39 0.39 8.54 2.22 0.61 ...
 $ Count_obs22 : num  0.39 0.39 3.05 1.22 1.22 ...
 $ Count_obs23 : num  0.39 0.78 6.1 0.78 0.61 ...
 $ Count_obs24 : num  0 0.78 4.27 0.78 0 ...
 $ Count_obs25 : num  0 0.78 6.71 0.61 0 ...
 $ Count_obs26 : num  0.78 0.78 7.32 2 0.61 ...
 $ Count_obs27 : num  0 1.95 4.27 0.61 0 ...
 $ Count_obs28 : num  0 1.17 4.88 1.78 1.22 ...
 $ Count_obs29 : num  0.78 0.78 3.05 0 0.61 ...
 $ Count_obs30 : num  0 0 3.66 1.83 0 ...
 $ Count_obs31 : num  0 1.17 4.27 1.39 1.22 ...
 $ Count_obs32 : num  0.39 0.78 7.93 0.61 1.22 ...
 $ Count_obs33 : num  0 0.78 9.76 0.78 1.22 ...
 $ Count_obs34 : num  0.78 1.17 6.71 0.61 0.61 ...
 $ Count_obs35 : num  0.39 0.39 7.93 1 0 ...
 $ Count_obs36 : num  0.78 0.39 6.1 1.22 1.22 ...
 $ Count_obs37 : num  0.39 0.78 6.71 2.61 3.05 ...
 $ Count_obs38 : num  0.39 0.78 5.49 1 0.61 ...
 $ Count_obs39 : num  1.56 0 4.27 2.22 0.61 ...
 $ Count_obs40 : num  0.39 0.78 8.54 0.78 1.22 ...
 $ Count_obs41 : num  0 0.78 7.32 0.61 0 ...
 $ Count_obs42 : num  0.78 0.39 9.15 0.39 0.61 ...
 $ Count_obs43 : num  0.39 0.78 3.66 0 0.61 ...
 $ Count_obs44 : num  0.39 1.17 4.27 0 0.61 ...
 $ Count_obs45 : num  0.78 1.56 4.88 1.39 2.44 ...
 $ Count_obs46 : num  0 1.17 6.71 0.61 0 ...
 $ Count_obs47 : num  0 0.39 9.15 1.61 0.61 ...
 $ Count_obs48 : num  0.39 0.78 6.1 1.61 0 ...
 $ Count_obs49 : num  0.78 0.78 6.1 1.56 0.61 ...
 $ Count_obs50 : num  0.78 0.78 3.66 0 1.22 ...
 $ Count_obs51 : num  0 0.78 6.1 2.22 0 ...
 $ Count_obs52 : num  0.39 1.17 4.88 0.61 0.61 ...
 $ Count_obs53 : num  0.39 0 7.32 1.39 1.22 ...
 $ Count_obs54 : num  0 0.78 7.32 1.78 2.44 ...
 $ Count_obs55 : num  0 1.56 8.54 0.61 0.61 ...
 $ Count_obs56 : num  0.78 1.56 7.32 1.39 0.61 ...
 $ Count_obs57 : num  0 0.78 7.93 0 0 ...
 $ Count_obs58 : num  1.17 1.17 7.32 2.61 1.22 ...
 $ Count_obs59 : num  0 0.39 6.1 0 1.22 ...
 $ Count_obs60 : num  0.78 0.78 6.71 1.22 0.61 ...
 $ Count_obs61 : num  0 1.17 5.49 0.39 1.22 ...
 $ Count_obs62 : num  1.17 0.78 6.1 1.22 0.61 ...
 $ Count_obs63 : num  0.39 1.95 3.66 0.39 0 ...
 $ Count_obs64 : num  0 0 6.71 1.83 0.61 ...
 $ Count_obs65 : num  0.78 0.78 8.54 0 1.22 ...
 $ Count_obs66 : num  0 0.39 6.1 1.39 0 ...
 $ Count_obs67 : num  1.17 0 3.66 0.39 0 ...
 $ Count_obs68 : num  0.78 0.78 7.93 1.22 0.61 ...
 $ Count_obs69 : num  0.39 1.17 6.1 0 0 ...
 $ Count_obs70 : num  0.39 0.78 5.49 1.78 0 ...
 $ Count_obs71 : num  0 1.56 6.1 2.17 0.61 ...
 $ Count_obs72 : num  0.78 0.78 6.1 0.61 0 ...
 $ Count_obs73 : num  0.39 1.17 4.88 0.39 2.44 ...
 $ Count_obs74 : num  0.78 1.17 6.71 1.61 0.61 ...
 $ Count_obs75 : num  1.17 1.17 12.2 0 0 ...
 $ Count_obs76 : num  0.39 0.39 7.32 0.61 1.22 ...
 $ Count_obs77 : num  0 0.78 7.93 0 0.61 ...
 $ Count_obs78 : num  0 0 7.93 0 1.22 ...
 $ Count_obs79 : num  1.17 0.78 8.54 0.39 1.22 ...
 $ Count_obs80 : num  0 1.17 7.93 1 0 ...
 $ Count_obs81 : num  0.78 0.78 7.93 0.39 0.61 ...
 $ Count_obs82 : num  0.39 0.78 3.66 0 0.61 ...
 $ Count_obs83 : num  0.78 0.39 4.88 1.61 1.22 ...
 $ Count_obs84 : num  0.39 0.78 7.93 0.61 0.61 ...
 $ Count_obs85 : num  1.17 0 8.54 1.61 0 ...
 $ Count_obs86 : num  0.78 0.39 4.88 0.61 0.61 ...
 $ Count_obs87 : num  0.39 0 6.71 1 0 ...
 $ Count_obs88 : num  0 2.34 9.15 2 0 ...
 $ Count_obs89 : num  0.39 0.78 5.49 1 0.61 ...
  [list output truncated]
 - attr(*, ".internal.selfref")=<externalptr>

I will see if consolidating documentations for all Count_Obs columns work.

marcnadon commented 5 years ago

Added information into previous comment.