rowRanks(x, rows=NULL, cols=NULL, ties.method=c("max", "average", "min"), dim.=dim(x),
...)
colRanks(x, rows=NULL, cols=NULL, ties.method=c("max", "average", "min"), dim.=dim(x),
preserveShape=FALSE, ...)character string specifying how ties are treated.
For details, see below.integer matrix is returned.
The rowRanks() function always returns an NxK matrix,
where N (K) is the number of rows (columns) whose ranks are calculated. The colRanks() function returns an NxK matrix,
if preserveShape = TRUE, otherwise a KxN matrix.
NA, as with na.last="keep"
in the rank() function.ties.method
specifies what their ranks should be.
If ties.method is "max", ties
are ranked as the maximum value.
If ties.method is "average", ties are ranked
by their average.
If ties.method is "max" ("min"), ties
are ranked as the maximum (minimum) value.
If ties.method is "average", ties are ranked
by their average.
For further details, see rank().x are collected as rows
of the result matrix. The column ranks of x are collected as rows
if preserveShape = FALSE, otherwise as columns. The implementation is optimized for both speed and memory.
To avoid coercing to doubles (and hence memory allocation), there
is a unique implementation for integer matrices.
It is more memory efficient to do
colRanks(x, preserveShape=TRUE) than
t(colRanks(x, preserveShape=FALSE)). Any names of x are ignored and absent in the result.rank().
For developers, see also Section 'Utility functions' in
'Writing R Extensions manual', particularly the native functions
R_qsort_I() and R_qsort_int_I().