diag {base} | R Documentation |
Extract or replace the diagonal of a matrix, or construct a diagonal matrix.
diag(x = 1, nrow, ncol, names = TRUE)
diag(x) <- value
x |
a matrix, vector or 1D |
nrow , ncol |
optional dimensions for the result when |
names |
(when |
value |
either a single value or a vector of length equal to that
of the current diagonal. Should be of a mode which can be coerced
to that of |
diag
has four distinct usages:
x
is a matrix, when it extracts the diagonal.
x
is missing and nrow
is specified, it returns
an identity matrix.
x
is a scalar (length-one vector) and the only
argument, it returns a square identity matrix of size given by the scalar.
x
is a ‘numeric’ (complex
,
numeric
, integer
, logical
, or
raw
) vector, either of length at least 2 or there
were further arguments. This returns a matrix with the given
diagonal and zero off-diagonal entries.
It is an error to specify nrow
or ncol
in the first case.
If x
is a matrix then diag(x)
returns the diagonal of
x
. The resulting vector will have names
if
names
is true and if the
matrix x
has matching column and rownames.
The replacement form sets the diagonal of the matrix x
to the
given value(s).
In all other cases the value is a diagonal matrix with nrow
rows and ncol
columns (if ncol
is not given the matrix
is square). Here nrow
is taken from the argument if specified,
otherwise inferred from x
: if that is a vector (or 1D array) of
length two or more, then its length is the number of rows, but if it
is of length one and neither nrow
nor ncol
is specified,
nrow = as.integer(x)
.
When a diagonal matrix is returned, the diagonal elements are one
except in the fourth case, when x
gives the diagonal elements:
it will be recycled or truncated as needed, but fractional recycling
and truncation will give a warning.
Using diag(x)
can have unexpected effects if x
is a
vector that could be of length one. Use diag(x, nrow =
length(x))
for consistent behaviour.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
dim(diag(3))
diag(10, 3, 4) # guess what?
all(diag(1:3) == {m <- matrix(0,3,3); diag(m) <- 1:3; m})
## other "numeric"-like diagonal matrices :
diag(c(1i,2i)) # complex
diag(TRUE, 3) # logical
diag(as.raw(1:3)) # raw
(D2 <- diag(2:1, 4)); typeof(D2) # "integer"
require(stats)
## diag(<var-cov-matrix>) = variances
diag(var(M <- cbind(X = 1:5, Y = rnorm(5))))
#-> vector with names "X" and "Y"
rownames(M) <- c(colnames(M), rep("", 3))
M; diag(M) # named as well
diag(M, names = FALSE) # w/o names