rowRank
Syntax
rowRank(X, [ascending=true], [groupNum], [ignoreNA=true], [tiesMethod=’min’], [percent=false])
Please see Row-Based Functions for the parameters and calculation rules.
Arguments
X is a matrix.
ascending is a Boolean value indicating whether the sorting is in ascending order. The default value is true (ascending).
groupNum is a positive integer indicating the number of groups to sort X into.
ignoreNA is a Boolean value indicating whether NULL values are ignored.
tiesMethod is a string indicating how to rank the group of elements with the same value (i.e., ties):
‘min’ : Gives all ties the smallest rank value of the tie values.
‘max’ : Gives all ties the largest rank value of the tie values.
‘average’ : Gives all ties the average of the rank values for all ties.
‘first’: Gives the first found tie value the lowest rank value, and continues with the following rank value for the next tie.
percent is a Boolean value, indicating whether to display the returned rankings in percentile form. The default value is false.
precision is an integer between [1, 15]. If the absolute difference between two values is no greater than 10^(-precision), the two values are considered to be equal.
Note: If parameter precision is specified, X must be numeric, and the tiesMethod cannot be specified as ‘first’.
Details
Conduct the following operation within each row of matrix X:
Return the position of each element in the sorted vector.
If groupNum is specified, group the elements into groupNum groups and return the group number each element belongs to.
If ignoreNA =true, NULL values return NULL.
The result is a matrix with the same shape as X.
Examples
$ m=matrix(3 1 2 4 7 6 9 8 5, 9 NULL 2 3 5 6 3 2 8).transpose();
$ m
#0 |
#1 |
#2 |
#3 |
#4 |
#5 |
#6 |
#7 |
#8 |
|---|---|---|---|---|---|---|---|---|
3 |
1 |
2 |
4 |
7 |
6 |
9 |
8 |
5 |
9 |
2 |
3 |
5 |
6 |
3 |
2 |
8 |
$ m.rowRank();
#0 |
#1 |
#2 |
#3 |
#4 |
#5 |
#6 |
#7 |
#8 |
|---|---|---|---|---|---|---|---|---|
2 |
0 |
1 |
3 |
6 |
5 |
8 |
7 |
4 |
7 |
0 |
2 |
4 |
5 |
2 |
0 |
6 |
$ m.rowRank(false);
#0 |
#1 |
#2 |
#3 |
#4 |
#5 |
#6 |
#7 |
#8 |
|---|---|---|---|---|---|---|---|---|
6 |
8 |
7 |
5 |
2 |
3 |
0 |
1 |
4 |
0 |
6 |
4 |
3 |
2 |
4 |
6 |
1 |
$ m.rowRank(groupNum=3);
#0 |
#1 |
#2 |
#3 |
#4 |
#5 |
#6 |
#7 |
#8 |
|---|---|---|---|---|---|---|---|---|
0 |
0 |
0 |
1 |
2 |
1 |
2 |
2 |
1 |
2 |
0 |
0 |
1 |
1 |
0 |
0 |
2 |
$ m.rowRank(ignoreNA=false);
#0 |
#1 |
#2 |
#3 |
#4 |
#5 |
#6 |
#7 |
#8 |
|---|---|---|---|---|---|---|---|---|
2 |
0 |
1 |
3 |
6 |
5 |
8 |
7 |
4 |
8 |
0 |
1 |
3 |
5 |
6 |
3 |
1 |
7 |
$ m.rowRank(ignoreNA=false, tiesMethod='max');
#0 |
#1 |
#2 |
#3 |
#4 |
#5 |
#6 |
#7 |
#8 |
|---|---|---|---|---|---|---|---|---|
2 |
0 |
1 |
3 |
6 |
5 |
8 |
7 |
4 |
8 |
0 |
2 |
4 |
5 |
6 |
4 |
2 |
7 |
$ m.rowRank(ignoreNA=false, tiesMethod='first');
col1 |
col2 |
col3 |
col4 |
col5 |
col6 |
col7 |
col8 |
col9 |
|---|---|---|---|---|---|---|---|---|
2 |
0 |
1 |
3 |
6 |
5 |
8 |
7 |
4 |
8 |
0 |
1 |
3 |
5 |
6 |
4 |
2 |
7 |
Related functions: rowDenseRank, rank