Simulated multi-objective data — sim_multi

Simulated data for prioritizing conservation projects based on multiple objectives.

Usage

data(sim_multi_actions)

data(sim_multi_projects)

data(sim_multi_features)

data(sim_multi_tree)

Format

sim_multi_projects: list of tibble::tibble() objects.
sim_multi_actions: tibble::tibble() object.
sim_multi_features: list of tibble::tibble() objects.
sim_multi_tree: list of ape::phylo() objects.

Details

The data set contains the following objects.

"sim_multi_projects"

A list of three tibble::tibble() objects containing data for simulated conservation projects. Each tibble::tibble() object corresponds to a different objective. Within each of these tibble::tibble() objects, each row corresponds to a different project and each column contains information about the projects. These tables contains the following columns.

"name": These columns contain the character name for each project.
"success": These columns contain the numeric probability of each project succeeding if it is funded.
"F1" ... "F5": These columns contain numeric values for each feature (i.e., "F1", "F2", "F3", "F4", ..., "F10") that indicate the probability that the feature will persist if each project is successfully completed. Missing values (NA) indicate that a feature does not benefit from a project being funded.
"A1" ... "A15": These columns contain logical (TRUE/FALSE) values for each action (i.e., "A1", "A2", ..., "A15") indicating if the action is associated with each project or not.
"baseline_action": These columns contain logical (TRUE/FALSE) values for each project indicating if the project is the baseline project or not.

sim_multi_actions

A tibble::tibble() object containing data for 15 simulated actions. Each row corresponds to a different action and each column contains information about the actions. This table contains the following columns.

"name": This column contains the character name for each action.
"cost": This column contains the numeric cost for each action.
"locked_in": This column contains logical values indicating if particular actions should be locked into the solution.
"locked_out": This column contains logical values indicating if particular actions should be locked out of the solution.

sim_multi_features

A list of three tibble::tibble() objects containing data for ten simulated features. Each tibble::tibble() object corresponds to a different objective. With each tibble::tibble() object, each row corresponds to a different feature and each column contains information about the features. These tables contains the following columns.

"name": These columns contain character values denoting name for each feature.
"weight": These columns contain numeric values denoting weight for each feature.

sim_multi_trees

A list of ape::phylo() phylogenetic tree objects for the features associated with each of the three objective.

Examples

# load data
data(sim_multi_projects)
data(sim_multi_actions)
data(sim_multi_features)
data(sim_multi_tree)

# print project data
print(sim_multi_projects)
#> $projects_obj1
#> # A tibble: 4 × 23
#>   name      success     F1     F2     F8 A1_action A2_action A3_action A4_action
#>   <chr>       <dbl>  <dbl>  <dbl>  <dbl> <lgl>     <lgl>     <lgl>     <lgl>    
#> 1 F1_proje…   0.832  0.798 NA     NA     TRUE      FALSE     TRUE      FALSE    
#> 2 F2_proje…   0.862 NA      0.693 NA     TRUE      TRUE      FALSE     FALSE    
#> 3 F8_proje…   0.964 NA     NA      0.555 TRUE      TRUE      TRUE      TRUE     
#> 4 baseline…   1      0.139  0.399  0.280 FALSE     FALSE     FALSE     FALSE    
#> # ℹ 14 more variables: A5_action <lgl>, A6_action <lgl>, A7_action <lgl>,
#> #   A8_action <lgl>, A9_action <lgl>, A10_action <lgl>, A11_action <lgl>,
#> #   A12_action <lgl>, A13_action <lgl>, A14_action <lgl>, A15_action <lgl>,
#> #   B1_action <lgl>, B2_action <lgl>, B3_action <lgl>
#> 
#> $projects_obj2
#> # A tibble: 3 × 22
#>   name  success     F3      F4 A1_action A2_action A3_action A4_action A5_action
#>   <chr>   <dbl>  <dbl>   <dbl> <lgl>     <lgl>     <lgl>     <lgl>     <lgl>    
#> 1 F3_p…   0.886  0.856 NA      TRUE      TRUE      FALSE     TRUE      TRUE     
#> 2 F4_p…   0.850 NA      0.733  TRUE      FALSE     TRUE      TRUE      TRUE     
#> 3 base…   1      0.381  0.0483 FALSE     FALSE     FALSE     FALSE     FALSE    
#> # ℹ 13 more variables: A6_action <lgl>, A7_action <lgl>, A8_action <lgl>,
#> #   A9_action <lgl>, A10_action <lgl>, A11_action <lgl>, A12_action <lgl>,
#> #   A13_action <lgl>, A14_action <lgl>, A15_action <lgl>, B1_action <lgl>,
#> #   B2_action <lgl>, B3_action <lgl>
#> 
#> $projects_obj3
#> # A tibble: 6 × 25
#>   name           success     F5     F6     F7     F9     F10 A1_action A2_action
#>   <chr>            <dbl>  <dbl>  <dbl>  <dbl>  <dbl>   <dbl> <lgl>     <lgl>    
#> 1 F5_project       0.834  0.755 NA     NA     NA     NA      TRUE      TRUE     
#> 2 F6_project       0.715 NA      0.739 NA     NA     NA      FALSE     FALSE    
#> 3 F7_project       0.890 NA     NA      0.588 NA     NA      FALSE     TRUE     
#> 4 F9_project       0.799 NA     NA     NA      0.593 NA      FALSE     FALSE    
#> 5 F10_project      0.919 NA     NA     NA     NA      0.745  TRUE      FALSE    
#> 6 baseline_proj…   1      0.382  0.151  0.369  0.332  0.0665 FALSE     FALSE    
#> # ℹ 16 more variables: A3_action <lgl>, A4_action <lgl>, A5_action <lgl>,
#> #   A6_action <lgl>, A7_action <lgl>, A8_action <lgl>, A9_action <lgl>,
#> #   A10_action <lgl>, A11_action <lgl>, A12_action <lgl>, A13_action <lgl>,
#> #   A14_action <lgl>, A15_action <lgl>, B1_action <lgl>, B2_action <lgl>,
#> #   B3_action <lgl>
#> 

# print action data
print(sim_multi_actions)
#> # A tibble: 18 × 4
#>    name        cost locked_in locked_out
#>    <chr>      <dbl> <lgl>     <lgl>     
#>  1 A1_action   94.4 FALSE     FALSE     
#>  2 A2_action  101.  FALSE     FALSE     
#>  3 A3_action  103.  FALSE     FALSE     
#>  4 A4_action   99.2 FALSE     FALSE     
#>  5 A5_action   99.9 FALSE     FALSE     
#>  6 A6_action  100.  FALSE     FALSE     
#>  7 A7_action   93.9 FALSE     FALSE     
#>  8 A8_action   91.7 TRUE      FALSE     
#>  9 A9_action  100.  FALSE     FALSE     
#> 10 A10_action  93.1 FALSE     FALSE     
#> 11 A11_action  99.7 FALSE     FALSE     
#> 12 A12_action  98.6 FALSE     TRUE      
#> 13 A13_action  88.8 FALSE     FALSE     
#> 14 A14_action  98.5 FALSE     FALSE     
#> 15 A15_action 102.  FALSE     FALSE     
#> 16 B1_action    0   FALSE     FALSE     
#> 17 B2_action    0   FALSE     FALSE     
#> 18 B3_action    0   FALSE     FALSE     

# print feature data
print(sim_multi_features)
#> [[1]]
#> # A tibble: 3 × 2
#>   name  weight
#>   <chr>  <dbl>
#> 1 F1     0.298
#> 2 F2     0.298
#> 3 F8     0.529
#> 
#> [[2]]
#> # A tibble: 2 × 2
#>   name  weight
#>   <chr>  <dbl>
#> 1 F3     0.438
#> 2 F4     0.438
#> 
#> [[3]]
#> # A tibble: 5 × 2
#>   name  weight
#>   <chr>  <dbl>
#> 1 F5    0.0211
#> 2 F6    0.0211
#> 3 F7    0.120 
#> 4 F9    0.137 
#> 5 F10   0.137 
#> 

# print phylogenetic trees
print(sim_multi_tree)
#> $tree_obj1
#> 
#> Phylogenetic tree with 3 tips and 2 internal nodes.
#> 
#> Tip labels:
#>   F1, F2, F8
#> 
#> Rooted; includes branch length(s).
#> 
#> $tree_obj2
#> 
#> Phylogenetic tree with 2 tips and 1 internal node.
#> 
#> Tip labels:
#>   F3, F4
#> 
#> Rooted; includes branch length(s).
#> 
#> $tree_obj3
#> 
#> Phylogenetic tree with 5 tips and 4 internal nodes.
#> 
#> Tip labels:
#>   F5, F6, F7, F9, F10
#> 
#> Rooted; includes branch length(s).
#>