Brat {VGAM} | R Documentation |
Takes in a square matrix of counts and outputs
them in a form that is accessible to the brat
and bratt
family functions.
Brat(mat, ties=0*mat, string=c(" > "," == "))
mat |
Matrix of counts, which is considered M by M in dimension when there are ties, and M+1 by M+1 when there are no ties. The rows are winners and the columns are losers, e.g., the 2-1 element is now many times Competitor 2 has beaten Competitor 1. The matrices are best labelled with the competitors' names. |
ties |
Matrix of counts. This should be the same
dimension as mat . By default, there are no ties.
The matrix must be symmetric, and the diagonal should contain
NA s.
|
string |
Character.
The matrices are labelled with the first value of the descriptor, e.g.,
"NZ > Oz" `means' NZ beats Australia in rugby.
Suggested alternatives include " beats " or " wins against " .
The second value is used to handle ties.
|
In the VGAM package
it is necessary for each matrix to be represented as a single
row of data by brat
and bratt
.
Hence the non-diagonal elements of the M+1 by M+1 matrix
are concatenated into M(M+1) values (no ties), while
if there are ties, the non-diagonal elements of the M by M matrix
are concatenated into M(M-1) values.
A matrix with 1 row and either M(M+1) or M(M-1) columns.
This is a data preprocessing function for
brat
and bratt
.
Yet to do: merge InverseBrat
into brat
.
T. W. Yee
Agresti, A. (2002) Categorical Data Analysis, 2nd ed. New York: Wiley.
journal = c("Biometrika", "Comm Statist", "JASA", "JRSS-B") m = matrix(c( NA, 33, 320, 284, 730, NA, 813, 276, 498, 68, NA, 325, 221, 17, 142, NA), 4,4) dimnames(m) = list(winner = journal, loser = journal) Brat(m) vglm(Brat(m) ~ 1, brat, trace=TRUE)