match.vec2mat: Transform a matching vector to a binary matching matrix
In hamlet: Hierarchical Optimal Matching and Machine Learning Toolbox

Description Usage Arguments Value Author(s) See Also Examples

This function allows transforming a matching vector to a binary matching matrix. A matching vector is of length N where each element indicates the submatch to which the observation belongs to. Notice that this is not the same as the group allocation vector that is provided by the match.allocate-function. The binary matching matrix is of size N x N where 0 indicates that the observations have been part of a different submatch, and 1 indicates that the observations have been part of the same submatch. Diagonal is always 0 although an observation is always in the same submatch with its self.

1	match.vec2mat(x)

`x`	A matching vector 'x'

N times N binary matching matrix, where 0 indicates that the observations have been part of a different submatch, and 1 indicates that the observations have been part of the same submatch.

Teemu Daniel Laajala <teelaa@utu.fi>

match.allocate match.mat2vec match.bb match.dummy

data(vcapwide)

# Construct an Euclidean distance example distance matrix using 15 observations from the VCaP study
d <- as.matrix(dist(vcapwide[1:15,c("PSAWeek10", "BWWeek10")]))

bb3 <- match.bb(d, g=3)
str(bb3)

solvec <- bb3$solution 
# matching vector, where each element indicates to which submatch each observation belongs to

solvec
mat <- match.vec2mat(solvec)
mat
which(mat[1,] == 1) 
# E.g. the first, third and thirteenth observation are part of the same submatch
which(solvec == solvec[1]) 
# Similarly

[1] "Performing initial sorting for a good initial guess"
[1] "Computing boundaries for minimum distances in possible combinations..."
[1] "Starting branch and bound"
[1] "Branches: 18"
[1] "Bounds: 357"
[1] "Ends visited: 4"
[1] "Solution cost 73.1793785290756"
[1] "Solution: 3,1,3,5,2,4,4,5,1,2,2,5,3,4,1"
List of 6
 $ branches: num 18
 $ bounds  : num 357
 $ ends    : num 4
 $ matrix  : num [1:15, 1:15] 0 0 1 0 0 0 0 0 0 0 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:15] "ID003" "ID007" "ID008" "ID009" ...
  .. ..$ : chr [1:15] "ID003" "ID007" "ID008" "ID009" ...
 $ solution: Named num [1:15] 3 1 3 5 2 4 4 5 1 2 ...
  ..- attr(*, "names")= chr [1:15] "ID003" "ID007" "ID008" "ID009" ...
 $ cost    : num 73.2
ID003 ID007 ID008 ID009 ID010 ID016 ID018 ID025 ID027 ID031 ID032 ID037 ID040 
    3     1     3     5     2     4     4     5     1     2     2     5     3 
ID045 ID047 
    4     1 
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
 [1,]    0    0    1    0    0    0    0    0    0     0     0     0     1
 [2,]    0    0    0    0    0    0    0    0    1     0     0     0     0
 [3,]    1    0    0    0    0    0    0    0    0     0     0     0     1
 [4,]    0    0    0    0    0    0    0    1    0     0     0     1     0
 [5,]    0    0    0    0    0    0    0    0    0     1     1     0     0
 [6,]    0    0    0    0    0    0    1    0    0     0     0     0     0
 [7,]    0    0    0    0    0    1    0    0    0     0     0     0     0
 [8,]    0    0    0    1    0    0    0    0    0     0     0     1     0
 [9,]    0    1    0    0    0    0    0    0    0     0     0     0     0
[10,]    0    0    0    0    1    0    0    0    0     0     1     0     0
[11,]    0    0    0    0    1    0    0    0    0     1     0     0     0
[12,]    0    0    0    1    0    0    0    1    0     0     0     0     0
[13,]    1    0    1    0    0    0    0    0    0     0     0     0     0
[14,]    0    0    0    0    0    1    1    0    0     0     0     0     0
[15,]    0    1    0    0    0    0    0    0    1     0     0     0     0
      [,14] [,15]
 [1,]     0     0
 [2,]     0     1
 [3,]     0     0
 [4,]     0     0
 [5,]     0     0
 [6,]     1     0
 [7,]     1     0
 [8,]     0     0
 [9,]     0     1
[10,]     0     0
[11,]     0     0
[12,]     0     0
[13,]     0     0
[14,]     0     0
[15,]     0     0
[1]  3 13
ID003 ID008 ID040 
    1     3    13