Sparse symmetric random matrix
R = sprandsym(S)
R = sprandsym(n,density)
R = sprandsym(n,density,rc)
R = sprandsym(n,density,rc,kind)
R = sprandsym(S,[],rc,3)
R = sprandsym(S) returns
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) returns
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) returns
a matrix with 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 (nonnegative) 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.
If kind = 1, R is generated by
random Jacobi rotation of a positive definite diagonal matrix. R has
the desired condition number exactly.
If kind = 2, R is a shifted sum
of outer products. R has the desired condition
number only approximately, but has less structure.
R = sprandsym(S,[],rc,3) has the same structure
as the matrix S and approximate condition number 1/rc.
sprandsym uses the same random number generator
as rand, randi, and randn.
You control this generator with rng.