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library( mau )
# Example without ties
d <- 10
n <- matrix( sample( x = 0:5, size = d * d, replace = TRUE ), d, d )
n <- n + t( n )
diag( n ) <- 0
g <- rowSums( n )
# Number of win matches for each team
w <- sapply( 1:d, FUN = function( i ) sample( x = 1:g[i], size = 1, replace = TRUE ) )
# Number of lost matches for ech team
l <- rowSums( n ) - w
r <- colley_rating( n, w, l )
print( r )## [[1]]
## [1] 4 5 1 8 7 9 2 3 10 6
##
## [[2]]
## [1] 0.9743290 0.9438679 1.2472056 0.5080681 0.7962257 0.4738533 1.1775906
## [8] 1.1011904 0.4446450 0.8330244A <- matrix( c( 0, 7, 21, 7, 0,
52, 0, 34, 25, 27,
24, 16, 0, 7, 3,
38, 17, 5, 0, 14,
45, 7, 30, 52, 0 ),
nrow = 5, ncol = 5 )
r <- od_rating( A )
print( r )## $r
## [,1]
## [1,] 20.09702
## [2,] 188.78533
## [3,] 41.79470
## [4,] 84.80018
## [5,] 279.80681
##
## $o
## [,1]
## [1,] 33.98927
## [2,] 151.57374
## [3,] 48.66316
## [4,] 82.04849
## [5,] 114.83557
##
## $d
## [,1]
## [1,] 1.6912590
## [2,] 0.8028894
## [3,] 1.1643379
## [4,] 0.9675509
## [5,] 0.4104102
##
## $iter
## [1] 27library( mau )
m <- 10
n <- 5
R <- matrix( runif( m * n ), m, n )
v <- sample( x = 50:100, size = n )
r <- borda_count( R, v )
print( r )## [[1]]
## [1] 5 3 2 9 4 6 10 8 7 1
##
## [[2]]
## [1] 2572 2962 3240 1556 2635 2438 1372 2143 2278 3554These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.