Description Usage Arguments Details Value Missing values Performance Author(s) See Also Examples
Gets the rank of the elements in each row (column) of a matrix.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41  colRanks(
x,
rows = NULL,
cols = NULL,
ties.method = c("max", "average", "first", "last", "random", "max", "min", "dense"),
dim. = dim(x),
preserveShape = FALSE,
...
)
rowRanks(
x,
rows = NULL,
cols = NULL,
ties.method = c("max", "average", "first", "last", "random", "max", "min", "dense"),
dim. = dim(x),
...
)
## S4 method for signature 'DelayedMatrix'
colRanks(
x,
rows = NULL,
cols = NULL,
ties.method = c("max", "average", "first", "last", "random", "max", "min", "dense"),
dim. = dim(x),
preserveShape = FALSE,
force_block_processing = FALSE,
...
)
## S4 method for signature 'DelayedMatrix'
rowRanks(
x,
rows = NULL,
cols = NULL,
ties.method = c("max", "average", "first", "last", "random", "max", "min", "dense"),
dim. = dim(x),
force_block_processing = FALSE,
...
)

x 
A NxK DelayedMatrix. 
rows 
A 
cols 
A 
ties.method 
A 
dim. 
An 
preserveShape 
A 
... 
Additional arguments passed to specific methods. 
force_block_processing 

These functions rank values and treats missing values the same way as
rank
().
For equal values ("ties"), argument ties.method
determines how these
are ranked among each other. More precisely, for the following values of
ties.method
, each index set of ties consists of:
"first"
 increasing values that are all unique
"last"
 decreasing values that are all unique
"min"
 identical values equaling the minimum of
their original ranks
"max"
 identical values equaling the maximum of
their original ranks
"average"
 identical values that equal the sample mean of
their original ranks. Because the average is calculated, the returned
ranks may be noninteger values
"random"
 randomly shuffled values of their original ranks.
"dense"
 increasing values that are all unique and,
contrary to "first"
, never contain any gaps
For more information on ties.method = "dense"
, see frank()
of
the data.table package.
For more information on the other alternatives, see rank
().
Note that, due to different randomization strategies, the shuffling order
produced by these functions when using ties.method = "random"
does
not reproduce that of rank
().
WARNING: For backwardcompatibility reasons, the default is
ties.method = "max"
, which differs from rank
()
which uses ties.method = "average"
by default.
Since we plan to change the default behavior in a future version, we recommend
to explicitly specify the intended value of argument ties.method
.
A matrix
of type integer
is
returned, unless ties.method = "average"
when it is of type
numeric
.
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
.
Any names
of x
are ignored and absent in the
result.
Missing values are ranked as NA_integer_
, as with na.last = "keep"
in the rank
() function.
The implementation is optimized for both speed and memory. To avoid
coercing to double
s (and hence memory allocation),
there is a unique implementation for integer
matrices.
Furthermore, it is more memory efficient to do
colRanks(x, preserveShape = TRUE)
than
t(colRanks(x, preserveShape = FALSE))
.
Peter Hickey
For developers, see also Section Utility functions' in
'Writing R Extensions manual', particularly the
native functions R_qsort_I()
and R_qsort_int_I()
.
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