R = sprandsym(S)
R = sprandsym(n,density)
R = sprandsym(n,density,rc)
R = sprandsym(n,density,rc,kind)
R = sprandsym(S)
is a symmetric random matrix whose lower triangle and diagonal have the same structure as S
. Its elements are normally distributed, with mean 0 and variance 1.
R = sprandsym(n,density)
is a symmetric random, n
-by-n
, sparse matrix with approximately density
*n
*n
nonzeros; each entry is the sum of one or more normally distributed random samples, and (0 <= density <= 1)
.
R = sprandsym(n,density,rc)
has a reciprocal condition number equal to rc
. The distribution of entries is nonuniform; it is roughly symmetric about 0; all are in [-1,1].
If rc
is a vector of length n
, then R
has eigenvalues rc
. Thus, if rc
is a positive (nonnegative) vector then R
is a positive definite matrix. In either case, R
is generated by random Jacobi rotations applied to a diagonal matrix with the given eigenvalues or condition number. It has a great deal of topological and algebraic structure.
R = sprandsym(n,
density,
rc,
kind)
is positive definite, where kind
can be:
1
to generate R
by random Jacobi rotation of a positive definite diagonal matrix. R
has the desired condition number exactly. 2
to generate an R
that is a shifted sum of outer products. R
has the desired condition number only approximately, but has less structure. 3
to generate an R
that has the same structure as the matrix S
and approximate condition number 1/rc
. density
is ignored.
sprandn
(c) Copyright 1994 by The MathWorks, Inc.