Perform additional scans and add them to the scanList New scans rely on edge probability matrix previously drawn from beta distributions. This can be used to compare sampling regime when it is expected that one will sample edges less in a predictable fashion (e.g. group-scan vs focal sampling)

Source: R/expDesign_building.blocks.R

Written as a S3 method to be applied to scanList or sLlist (list of scanList) objects.

add_scans(scan.list, ...)

Arguments

scan.list

a scanList or sLlist object. See objects returned by simunet()
...

additional arguments to be passed. At the moment scale_scans() does not use

add_scans() can use argument:

  • new.scans: integer scalar, the number of additional new scans to be performed and added to the scan.list

Value

a scanList, or list of such, to which additional scans have been added to the 3D array. See also simunet().

Also modifies these attributes to attrs:

  • n.scans: integer indicating how many scans have been performed in total. n.scans itself has the attribute scans.performed that keeps track of what "batches" of scans have been performed, by growing a vector of "scan batch" sizes

See also

simunet(), design_exp(), perform_exp().

Examples

set.seed(42)
n <- 5L
samp.effort <- 241L

# Adjacency matrix import
## random directed adjacency matrix
Adj <- sample(1:samp.effort,n * n) |>
  matrix(nrow = 5,dimnames = list(letters[1:n],letters[1:n]))
diag(Adj) <- 0L
Adj

#>     a   b   c   d   e
#> a   0 228  47 165 111
#> b 229   0  24 110 131
#> c  65 122   0  20  41
#> d 153 241 100   0 227
#> e  74 128  89 114   0

# social network simulations
## theoretical scans
sL <- simunet(Adj = Adj,samp.effort = samp.effort,mode = "directed",n.scans = 120L)
sL

#> 
#> scan: 1           
#> a . 1 . 1 .
#> b 1 . . . .
#> c . . . . .
#> d . 1 1 . 1
#> e . . 1 . .
#> 
#> scan: 2           
#> a . 1 . . .
#> b 1 . . 1 .
#> c 1 1 . . .
#> d . 1 . . 1
#> e . . 1 1 .
#> 
#> ... ( 117  more scans)
#> 
#> scan: 120           
#> a . 1 . 1 1
#> b 1 . . 1 .
#> c . 1 . . .
#> d 1 1 . . 1
#> e . 1 1 . .
#> 
#> 
#> Hidden attributes:
#> scanList.type - raw.scanList - Adj - samp.effort - n.scans - mode
#> Adj.subfun - edge.Prob

## focal-scan sampling
sL |> perform_exp(design_sampling("focal","even")) |> add_scans(50)

#> 
#> scan: 1               
#> a .  1  .  1  .
#> b 1  . NA NA NA
#> c . NA  . NA NA
#> d . NA NA  . NA
#> e . NA NA NA  .
#> 
#> scan: 2               
#> a  . NA NA . NA
#> b NA  . NA 1 NA
#> c NA NA  . . NA
#> d  .  1  . .  1
#> e NA NA NA 1  .
#> 
#> ... ( 167  more scans)
#> 
#> scan: 170           
#> a . 1 . 1 .
#> b 1 . 1 1 1
#> c . 1 . . .
#> d . 1 . . 1
#> e . . 1 1 .
#> 
#> 
#> Hidden attributes:
#> scanList.type - raw.scanList - Adj - samp.effort - n.scans - mode
#> Adj.subfun - edge.Prob - focalList - theoretical.scanList